. clear all

. cap noi which tabout
C:\Users\CISS Fondecyt\ado\plus\t\tabout.ado
*! 2.0.8 Ian Watson 15mar2019
*! tabout version 3 (beta) available at: http://tabout.net.au

. if _rc==111 {
.         cap noi ssc install tabout
.         }

. cap noi which pathutil
C:\Users\CISS Fondecyt\ado\plus\p\pathutil.ado
*! version 2.2.0 19nov2020 daniel klein

. if _rc==111 {
.         cap noi net install pathutil, from("http://fmwww.bc.edu/repec/bocode/p/") 
.         }

. cap noi which pathutil
C:\Users\CISS Fondecyt\ado\plus\p\pathutil.ado
*! version 2.2.0 19nov2020 daniel klein

. if _rc==111 {
.         ssc install dirtools    
.         }

. cap noi which project
C:\Users\CISS Fondecyt\ado\plus\p\project.ado
*! version 1.3.1  22dec2013  picard@netbox.com

. if _rc==111 {   
.         ssc install project
.         }

. cap noi which stipw
C:\Users\CISS Fondecyt\ado\plus\s\stipw.ado
*! Version 1.0.0 17Jan2022

. if _rc==111 {   
.         ssc install stipw
.         }

. cap noi which stpm2
C:\Users\CISS Fondecyt\ado\plus\s\stpm2.ado
*! version 1.7.5 May2021

. if _rc==111 {   
.         ssc install stpm2
.         }       

. cap noi which rcsgen
C:\Users\CISS Fondecyt\ado\plus\r\rcsgen.ado
*! version 1.5.9 13FEB2022

. if _rc==111 {   
.         ssc install rcsgen
.         }       

. cap noi which matselrc
C:\Users\CISS Fondecyt\ado\plus\m\matselrc.ado
*! NJC 1.1.0 20 Apr 2000  (STB-56: dm79)

. if _rc==111 {           
. cap noi net install dm79, from(http://www.stata.com/stb/stb56)
.         }

. cap noi which stpm2_standsurv
C:\Users\CISS Fondecyt\ado\plus\s\stpm2_standsurv.ado
*! version 1.1.2 12Jun2018 

. if _rc==111 {           
. cap noi net install stpm2_standsurv.pkg, from(http://fmwww.bc.edu/RePEc/bocode/s)
.         }

. cap noi which fs
C:\Users\CISS Fondecyt\ado\plus\f\fs.ado
*! NJC 1.0.5 23 November 2006 

. if _rc==111 {           
.         ssc install fs
.         }

. cap noi which mkspline2
C:\Users\CISS Fondecyt\ado\plus\m\mkspline2.ado
*! version 1.0.0 MLB 04Apr2009

. if _rc==111 {           
.         ssc install postrcspline
.         }

.         
. cap noi which evalue
C:\Users\CISS Fondecyt\ado\plus\e\evalue.ado
*! 1.3.0 Ariel Linden 23Sep2019 // changed instances of "substr()" to "substr()" because of Stata version issues
*! 1.2.0 Ariel Linden 05Aug2019 // made "rare" the default for OR and HR, and made "common" the user-specified option
*! 1.1.0 Ariel Linden 26Jan2019 // added figure option, streamlined code
*! 1.0.0 Ariel Linden 24Jan2019

. if _rc==111 {           
.         ssc install evalue
.         }       

Summary tables

#################################################_

#################################################_

Condemnatory_Sentence_Listwise_Main

#################################################_

Survival

. cap qui noi use "mariel_feb_23.dta", clear

. *estread using "mariel_feb_23.sters", replace
. 
. keep s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci tt

. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as11 = (ests_s_tr_comp , ests_s_tr_comp_lci, ests_s_tr_comp_uci ,  ///
>         ests_s_early_drop , ests_s_early_drop_lci, ests_s_early_drop_uci , ///
>         ests_s_late_drop , ests_s_late_drop_lci , ests_s_late_drop_uci )

. matrix colnames est_as11 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as11) using "${pathdata2}prob_condsent_m0_main.html", replace 
(output written to prob_condsent_m0_main.html)

RMST

. cap qui noi use "mariel_feb_23.dta", clear

. *estread using "mariel_feb_23.sters", replace
. 
. keep rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci tt

. 
. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as12 = (ests_rmst_h0 , ests_rmst_h0_lci , ests_rmst_h0_uci ,  ///
>         ests_rmst_h1 , ests_rmst_h1_lci , ests_rmst_h1_uci ,  ///
>         ests_rmst_h2 , ests_rmst_h2_lci , ests_rmst_h2_uci )

. matrix colnames est_as12 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as12) using "${pathdata2}rmst_condsent_m0_main.html", replace 
(output written to rmst_condsent_m0_main.html)

Difference Survival

. cap qui noi use "mariel_feb_23.dta", clear

. *estread using "mariel_feb_23.sters", replace
. 
. keep sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_late_drop_uci sdif
> f_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci tt

. 
. foreach var of varlist sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_
> late_drop_uci sdiff_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 2, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci  diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_d
> rop_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as13 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as13 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as13) using "${pathdata2}prob_condsent_m0_main_diff.html", replace 
(output written to prob_condsent_m0_main_diff.html)

Difference RMST

. cap qui noi use "mariel_feb_23.dta", clear

. *estread using "mariel_feb_23.sters", replace
. 
. keep rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci rmstdiff_tr_comp_l
> ate_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci tt

. 
. foreach var of varlist rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci 
> rmstdiff_tr_comp_late_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 5, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_dr
> op_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as14 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as14 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as14) using "${pathdata2}rmst_condsent_m0_main_diff.html", replace 
(output written to rmst_condsent_m0_main_diff.html)

Condemnatory_Sentence_Listwise_IPW

Difference Survival

. cap qui noi use "mariel_feb_23.dta", clear

. *estread using "mariel_feb_23.sters", replace
. 
. keep sdiff_comp_vs_late sdiff_comp_vs_late_lci sdiff_comp_vs_late_uci sdiff_comp_vs_early sdiff_comp_vs_early_lci sdiff_comp_vs_early_uci sdiff_late_vs_early sdiff_late_vs_e
> arly_lci sdiff_late_vs_early_uci tt

. 
. foreach var of varlist sdiff_comp_vs_late sdiff_comp_vs_late_lci sdiff_comp_vs_late_uci sdiff_comp_vs_early sdiff_comp_vs_early_lci sdiff_comp_vs_early_uci sdiff_late_vs_ear
> ly sdiff_late_vs_early_lci sdiff_late_vs_early_uci {
  2.     local newname = substr("`var'", 2, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_comp_vs_late diff_comp_vs_late_lci diff_comp_vs_late_uci diff_comp_vs_early diff_comp_vs_early_lci diff_comp_vs_early_uci diff_late_vs_early diff
> _late_vs_early_lci diff_late_vs_early_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .20, .30) // tolerance of .06
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .40, .60) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .75, 1.25) // tolerance of .16
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.80, 3.20) // tolerance of .40
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.50, 5.50) // tolerance of .40
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as15 = (ests_diff_comp_vs_late , ests_diff_comp_vs_late_lci , ests_diff_comp_vs_late_uci ,  ///
>         ests_diff_comp_vs_early , ests_diff_comp_vs_early_lci, ests_diff_comp_vs_early_uci , ///
>         ests_diff_late_vs_early , ests_diff_late_vs_early_lci , ests_diff_late_vs_early_uci )

. matrix colnames est_as15 = Comp_Late Comp_Late_lci Comp_Late_uci Comp_Early Comp_Early_lci Comp_Early_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as15) using "${pathdata2}prob_condsent_m0_IPW_diff.html", replace 
(output written to prob_condsent_m0_IPW_diff.html)

Difference RMST

. cap qui noi use "mariel_feb_23.dta", clear

. *estread using "mariel_feb_23.sters", replace
. 
. keep rmstdiff_comp_vs_late rmstdiff_comp_vs_late_lci rmstdiff_comp_vs_late_uci rmstdiff_comp_vs_early rmstdiff_comp_vs_early_lci rmstdiff_comp_vs_early_uci rmstdiff_late_vs_
> early rmstdiff_late_vs_early_lci rmstdiff_late_vs_early_uci tt

. 
. foreach var of varlist rmstdiff_comp_vs_late rmstdiff_comp_vs_late_lci rmstdiff_comp_vs_late_uci rmstdiff_comp_vs_early rmstdiff_comp_vs_early_lci rmstdiff_comp_vs_early_uci
>  rmstdiff_late_vs_early rmstdiff_late_vs_early_lci rmstdiff_late_vs_early_uci {
  2.     local newname = substr("`var'", 5, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_comp_vs_late diff_comp_vs_late_lci diff_comp_vs_late_uci diff_comp_vs_early diff_comp_vs_early_lci diff_comp_vs_early_uci diff_late_vs_early diff
> _late_vs_early_lci diff_late_vs_early_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .20, .30) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .40, .60) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .75, 1.25) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.80, 3.20) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.50, 5.50) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as16 = (ests_diff_comp_vs_early , ests_diff_comp_vs_early_lci, ests_diff_comp_vs_early_uci ,  ///
>         ests_diff_comp_vs_late , ests_diff_comp_vs_late_lci , ests_diff_comp_vs_late_uci , ///
>         ests_diff_late_vs_early , ests_diff_late_vs_early_lci , ests_diff_late_vs_early_uci )

. matrix colnames est_as16 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as16) using "${pathdata2}rmst_condsent_m0_main_IPW_diff.html", replace 
(output written to rmst_condsent_m0_main_IPW_diff.html)

#################################################_

#################################################_

Condemnatory_Sentence_Imputed_Main

#################################################_

Survival

. cap qui noi use "mariel_feb_23_m1.dta", clear

. 
. keep s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci tt

. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as11m1 = (ests_s_tr_comp , ests_s_tr_comp_lci, ests_s_tr_comp_uci ,  ///
>         ests_s_early_drop , ests_s_early_drop_lci, ests_s_early_drop_uci , ///
>         ests_s_late_drop , ests_s_late_drop_lci , ests_s_late_drop_uci )

. matrix colnames est_as11m1 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as11m1) using "${pathdata2}prob_condsent_m1_main.html", replace 
(output written to prob_condsent_m1_main.html)

RMST

. cap qui noi use "mariel_feb_23_m1.dta", clear

. 
. keep rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci tt

. 
. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as12m1 = (ests_rmst_h0 , ests_rmst_h0_lci , ests_rmst_h0_uci ,  ///
>         ests_rmst_h1 , ests_rmst_h1_lci , ests_rmst_h1_uci ,  ///
>         ests_rmst_h2 , ests_rmst_h2_lci , ests_rmst_h2_uci )

. matrix colnames est_as12m1 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as12m1) using "${pathdata2}rmst_condsent_m1_main.html", replace 
(output written to rmst_condsent_m1_main.html)

Difference Survival

. cap qui noi use "mariel_feb_23_m1.dta", clear

. 
. keep sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_late_drop_uci sdif
> f_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci tt

. 
. foreach var of varlist sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_
> late_drop_uci sdiff_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 2, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci  diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_d
> rop_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as13m1 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as13m1 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as13m1) using "${pathdata2}prob_condsent_m1_main_diff.html", replace 
(output written to prob_condsent_m1_main_diff.html)

Difference RMST

. cap qui noi use "mariel_feb_23_m1.dta", clear

. 
. keep rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci rmstdiff_tr_comp_l
> ate_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci tt

. 
. foreach var of varlist rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci 
> rmstdiff_tr_comp_late_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 5, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_dr
> op_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .10, .30) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .35, .65) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as14m1 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as14m1 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as14m1) using "${pathdata2}rmst_condsent_m1_main_diff.html", replace 
(output written to rmst_condsent_m1_main_diff.html)

Condemnatory_Sentence_Imputed_IPW

Difference Survival

. cap qui noi use "mariel_feb_23_m1.dta", clear

. *estread using "mariel_feb_23.sters", replace
. 
. keep sdiff_comp_vs_late sdiff_comp_vs_late_lci sdiff_comp_vs_late_uci sdiff_comp_vs_early sdiff_comp_vs_early_lci sdiff_comp_vs_early_uci sdiff_late_vs_early sdiff_late_vs_e
> arly_lci sdiff_late_vs_early_uci tt2

. 
. foreach var of varlist sdiff_comp_vs_late sdiff_comp_vs_late_lci sdiff_comp_vs_late_uci sdiff_comp_vs_early sdiff_comp_vs_early_lci sdiff_comp_vs_early_uci sdiff_late_vs_ear
> ly sdiff_late_vs_early_lci sdiff_late_vs_early_uci {
  2.     local newname = substr("`var'", 2, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_comp_vs_late diff_comp_vs_late_lci diff_comp_vs_late_uci diff_comp_vs_early diff_comp_vs_early_lci diff_comp_vs_early_uci diff_late_vs_early diff
> _late_vs_early_lci diff_late_vs_early_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt2, .10, .30) // tolerance of .06
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt2, .35, .65) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt2, .75, 1.25) // tolerance of .16
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt2, 2.80, 3.20) // tolerance of .40
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt2,  4.50, 5.50) // tolerance of .40
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as15m1 = (ests_diff_comp_vs_late , ests_diff_comp_vs_late_lci , ests_diff_comp_vs_late_uci ,  ///
>         ests_diff_comp_vs_early , ests_diff_comp_vs_early_lci, ests_diff_comp_vs_early_uci , ///
>         ests_diff_late_vs_early , ests_diff_late_vs_early_lci , ests_diff_late_vs_early_uci )

. matrix colnames est_as15m1 = Comp_Late Comp_Late_lci Comp_Late_uci Comp_Early Comp_Early_lci Comp_Early_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as15m1) using "${pathdata2}prob_condsent_m1_IPW_diff.html", replace 
(output written to prob_condsent_m1_IPW_diff.html)

Difference RMST

. cap qui noi use "mariel_feb_23_m1.dta", clear

. *estread using "mariel_feb_23.sters", replace
. 
. keep rmstdiff_comp_vs_late rmstdiff_comp_vs_late_lci rmstdiff_comp_vs_late_uci rmstdiff_comp_vs_early rmstdiff_comp_vs_early_lci rmstdiff_comp_vs_early_uci rmstdiff_late_vs_
> early rmstdiff_late_vs_early_lci rmstdiff_late_vs_early_uci tt2

. 
. foreach var of varlist rmstdiff_comp_vs_late rmstdiff_comp_vs_late_lci rmstdiff_comp_vs_late_uci rmstdiff_comp_vs_early rmstdiff_comp_vs_early_lci rmstdiff_comp_vs_early_uci
>  rmstdiff_late_vs_early rmstdiff_late_vs_early_lci rmstdiff_late_vs_early_uci {
  2.     local newname = substr("`var'", 5, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_comp_vs_late diff_comp_vs_late_lci diff_comp_vs_late_uci diff_comp_vs_early diff_comp_vs_early_lci diff_comp_vs_early_uci diff_late_vs_early diff
> _late_vs_early_lci diff_late_vs_early_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt2, .10, .30) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt2, .35, .65) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt2, .75, 1.25) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt2, 2.80, 3.20) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt2,  4.50, 5.50) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as16m1 = (ests_diff_comp_vs_early , ests_diff_comp_vs_early_lci, ests_diff_comp_vs_early_uci ,  ///
>         ests_diff_comp_vs_late , ests_diff_comp_vs_late_lci , ests_diff_comp_vs_late_uci , ///
>         ests_diff_late_vs_early , ests_diff_late_vs_early_lci , ests_diff_late_vs_early_uci )

. matrix colnames est_as16m1 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as16m1) using "${pathdata2}rmst_condsent_m1_main_IPW_diff.html", replace 
(output written to rmst_condsent_m1_main_IPW_diff.html)

#################################################_

#################################################_

Condemnatory_Sentence_Imputed(2)_Main

#################################################_

Survival

. cap qui noi use "mariel_feb_23_m2.dta", clear

. 
. keep s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci tt

. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as11m2 = (ests_s_tr_comp , ests_s_tr_comp_lci, ests_s_tr_comp_uci ,  ///
>         ests_s_early_drop , ests_s_early_drop_lci, ests_s_early_drop_uci , ///
>         ests_s_late_drop , ests_s_late_drop_lci , ests_s_late_drop_uci )

. matrix colnames est_as11m2 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as11m2) using "${pathdata2}prob_condsent_m2_main.html", replace 
(output written to prob_condsent_m2_main.html)

RMST

. cap qui noi use "mariel_feb_23_m2.dta", clear

. 
. keep rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci tt

. 
. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as12m2 = (ests_rmst_h0 , ests_rmst_h0_lci , ests_rmst_h0_uci ,  ///
>         ests_rmst_h1 , ests_rmst_h1_lci , ests_rmst_h1_uci ,  ///
>         ests_rmst_h2 , ests_rmst_h2_lci , ests_rmst_h2_uci )

. matrix colnames est_as12m2 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as12m2) using "${pathdata2}rmst_condsent_m2_main.html", replace 
(output written to rmst_condsent_m2_main.html)

Difference Survival

. cap qui noi use "mariel_feb_23_m2.dta", clear

. 
. keep sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_late_drop_uci sdif
> f_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci tt

. 
. foreach var of varlist sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_
> late_drop_uci sdiff_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 2, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci  diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_d
> rop_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as13m2 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as13m2 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as13m2) using "${pathdata2}prob_condsent_m2_main_diff.html", replace 
(output written to prob_condsent_m2_main_diff.html)

Difference RMST

. cap qui noi use "mariel_feb_23_m2.dta", clear

. 
. 
. keep rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci rmstdiff_tr_comp_l
> ate_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci tt

. 
. foreach var of varlist rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci 
> rmstdiff_tr_comp_late_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 5, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_dr
> op_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as14m2 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as14m2 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as14m2) using "${pathdata2}rmst_condsent_m2_main_diff.html", replace 
(output written to rmst_condsent_m2_main_diff.html)

#################################################_

#################################################_

Imprisonment_Listwise_Main

#################################################_

Survival

. cap qui noi use "mariel_feb_23_2.dta", clear

. *estread using "mariel_feb_23_2".sters", replace
. 
. keep s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci tt

. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as21 = (ests_s_tr_comp , ests_s_tr_comp_lci, ests_s_tr_comp_uci ,  ///
>         ests_s_early_drop , ests_s_early_drop_lci, ests_s_early_drop_uci , ///
>         ests_s_late_drop , ests_s_late_drop_lci , ests_s_late_drop_uci )

. matrix colnames est_as21 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as21) using "${pathdata2}prob_prison_m0_main.html", replace 
(output written to prob_prison_m0_main.html)

RMST

. cap qui noi use "mariel_feb_23_2.dta", clear

. *estread using "mariel_feb_23_2".sters", replace
. 
. keep rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci tt

. 
. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .25) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .50) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.0) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.0) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.00) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as22 = (ests_rmst_h0 , ests_rmst_h0_lci , ests_rmst_h0_uci ,  ///
>         ests_rmst_h1 , ests_rmst_h1_lci , ests_rmst_h1_uci ,  ///
>         ests_rmst_h2 , ests_rmst_h2_lci , ests_rmst_h2_uci )

. matrix colnames est_as22 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as22) using "${pathdata2}rmst_prison_m0_main.html", replace 
(output written to rmst_prison_m0_main.html)

Difference Survival

. cap qui noi use "mariel_feb_23_2.dta", clear

. *estread using "mariel_feb_23_2.sters", replace
. 
. keep sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_late_drop_uci sdif
> f_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci tt

. 
. foreach var of varlist sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_
> late_drop_uci sdiff_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 2, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci  diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_d
> rop_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as23 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as23 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as23) using "${pathdata2}prob_prison_m0_main_diff.html", replace 
(output written to prob_prison_m0_main_diff.html)

Difference RMST

. cap qui noi use "mariel_feb_23_2.dta", clear

. *estread using "mariel_feb_23_2.sters", replace
. 
. keep rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci rmstdiff_tr_comp_l
> ate_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci tt

. 
. foreach var of varlist rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci 
> rmstdiff_tr_comp_late_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 5, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_dr
> op_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as24 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as24 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as24) using "${pathdata2}rmst_prison_m0_main_diff.html", replace 
(output written to rmst_prison_m0_main_diff.html)

Imprisonment, Listwise, IPW

Difference Survival

. cap qui noi use "mariel_feb_23_2.dta", clear

. 
. *estread using "mariel_feb_23_2.sters", replace
. 
. keep sdiff_comp_vs_late sdiff_comp_vs_late_lci sdiff_comp_vs_late_uci sdiff_comp_vs_early sdiff_comp_vs_early_lci sdiff_comp_vs_early_uci sdiff_late_vs_early sdiff_late_vs_e
> arly_lci sdiff_late_vs_early_uci tt2

. 
. foreach var of varlist sdiff_comp_vs_late sdiff_comp_vs_late_lci sdiff_comp_vs_late_uci sdiff_comp_vs_early sdiff_comp_vs_early_lci sdiff_comp_vs_early_uci sdiff_late_vs_ear
> ly sdiff_late_vs_early_lci sdiff_late_vs_early_uci {
  2.     local newname = substr("`var'", 2, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_comp_vs_late diff_comp_vs_late_lci diff_comp_vs_late_uci diff_comp_vs_early diff_comp_vs_early_lci diff_comp_vs_early_uci diff_late_vs_early diff
> _late_vs_early_lci diff_late_vs_early_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt2, .10, .30) // tolerance of .06
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt2, .35, .65) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt2, .75, 1.25) // tolerance of .16
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt2, 2.80, 3.20) // tolerance of .40
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt2,  4.50, 5.50) // tolerance of .40
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as25 = (ests_diff_comp_vs_late , ests_diff_comp_vs_late_lci , ests_diff_comp_vs_late_uci ,  ///
>         ests_diff_comp_vs_early , ests_diff_comp_vs_early_lci, ests_diff_comp_vs_early_uci , ///
>         ests_diff_late_vs_early , ests_diff_late_vs_early_lci , ests_diff_late_vs_early_uci )

. matrix colnames est_as25 = Comp_Late Comp_Late_lci Comp_Late_uci Comp_Early Comp_Early_lci Comp_Early_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. *cap qui noi use "mariel_feb_23_2_early.dta", clear
. *qui ds
. *di word("`r(varlist)'", `c(k)')
. *browse 
. *NO EXTRAPOLA, REEMPLAZAR CON CERO EN UNA DE ESAS. NO EXTRAPOLA PORQUE LA PROBABILIDAD ES 1.
. 
. *cap qui noi use "mariel_feb_23_2_early_late.dta", clear
. *browse
. *NO HAY 6 MESES EN EARLY-LATE, SON SÓLO .78, que termina siendo absorvido por el año
. 
. esttab matrix(est_as25) using "${pathdata2}prob_prison_m0_IPW_diff.html", replace 
(output written to prob_prison_m0_IPW_diff.html)

Difference RMST

. cap qui noi use "mariel_feb_23_2.dta", clear

. *estread using "mariel_feb_23_2.sters", replace
. 
. keep rmstdiff_comp_vs_late rmstdiff_comp_vs_late_lci rmstdiff_comp_vs_late_uci rmstdiff_comp_vs_early rmstdiff_comp_vs_early_lci rmstdiff_comp_vs_early_uci rmstdiff_late_vs_
> early rmstdiff_late_vs_early_lci rmstdiff_late_vs_early_uci tt2

. 
. foreach var of varlist rmstdiff_comp_vs_late rmstdiff_comp_vs_late_lci rmstdiff_comp_vs_late_uci rmstdiff_comp_vs_early rmstdiff_comp_vs_early_lci rmstdiff_comp_vs_early_uci
>  rmstdiff_late_vs_early rmstdiff_late_vs_early_lci rmstdiff_late_vs_early_uci {
  2.     local newname = substr("`var'", 5, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_comp_vs_late diff_comp_vs_late_lci diff_comp_vs_late_uci diff_comp_vs_early diff_comp_vs_early_lci diff_comp_vs_early_uci diff_late_vs_early diff
> _late_vs_early_lci diff_late_vs_early_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt2, .10, .30) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt2, .35, .65) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt2, .75, 1.25) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt2, 2.80, 3.20) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt2,  4.50, 5.50) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as26 = (ests_diff_comp_vs_early , ests_diff_comp_vs_early_lci, ests_diff_comp_vs_early_uci ,  ///
>         ests_diff_comp_vs_late , ests_diff_comp_vs_late_lci , ests_diff_comp_vs_late_uci , ///
>         ests_diff_late_vs_early , ests_diff_late_vs_early_lci , ests_diff_late_vs_early_uci )

. matrix colnames est_as26 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as26) using "${pathdata2}rmst_prison_m0_main_IPW_diff.html", replace 
(output written to rmst_prison_m0_main_IPW_diff.html)

#################################################_

#################################################_

Imprisonment_Imputed_Main

#################################################_

Survival

. cap qui noi use "mariel_feb_23_2_m1.dta", clear

. 
. keep s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci tt

. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as21m1 = (ests_s_tr_comp , ests_s_tr_comp_lci, ests_s_tr_comp_uci ,  ///
>         ests_s_early_drop , ests_s_early_drop_lci, ests_s_early_drop_uci , ///
>         ests_s_late_drop , ests_s_late_drop_lci , ests_s_late_drop_uci )

. matrix colnames est_as21m1 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as21m1) using "${pathdata2}prob_prison_m1_main.html", replace 
(output written to prob_prison_m1_main.html)

RMST

. cap qui noi use "mariel_feb_23_2_m1.dta", clear

. 
. keep rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci tt

. 
. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as22m1 = (ests_rmst_h0 , ests_rmst_h0_lci , ests_rmst_h0_uci ,  ///
>         ests_rmst_h1 , ests_rmst_h1_lci , ests_rmst_h1_uci ,  ///
>         ests_rmst_h2 , ests_rmst_h2_lci , ests_rmst_h2_uci )

. matrix colnames est_as22m1 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as22m1) using "${pathdata2}rmst_prison_m1_main.html", replace 
(output written to rmst_prison_m1_main.html)

Difference Survival

. cap qui noi use "mariel_feb_23_2_m1.dta", clear

. 
. keep sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_late_drop_uci sdif
> f_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci tt

. 
. foreach var of varlist sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_
> late_drop_uci sdiff_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 2, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci  diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_d
> rop_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as23m1 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as23m1 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as23m1) using "${pathdata2}prob_prison_m1_main_diff.html", replace 
(output written to prob_prison_m1_main_diff.html)

Difference RMST

. cap qui noi use "mariel_feb_23_2_m1.dta", clear

. 
. keep rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci rmstdiff_tr_comp_l
> ate_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci tt

. 
. foreach var of varlist rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci 
> rmstdiff_tr_comp_late_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 5, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_dr
> op_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as24m1 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as24m1 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as24m1) using "${pathdata2}rmst_prison_m1_main_diff.html", replace 
(output written to rmst_prison_m1_main_diff.html)

Imprisonment, Imputed, IPW

Difference Survival

. cap qui noi use "mariel_feb_23_2_m1.dta", clear

. 
. *estread using "mariel_feb_23_2.sters", replace
. 
. keep sdiff_comp_vs_late sdiff_comp_vs_late_lci sdiff_comp_vs_late_uci sdiff_comp_vs_early sdiff_comp_vs_early_lci sdiff_comp_vs_early_uci sdiff_late_vs_early sdiff_late_vs_e
> arly_lci sdiff_late_vs_early_uci tt2

. 
. foreach var of varlist sdiff_comp_vs_late sdiff_comp_vs_late_lci sdiff_comp_vs_late_uci sdiff_comp_vs_early sdiff_comp_vs_early_lci sdiff_comp_vs_early_uci sdiff_late_vs_ear
> ly sdiff_late_vs_early_lci sdiff_late_vs_early_uci {
  2.     local newname = substr("`var'", 2, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_comp_vs_late diff_comp_vs_late_lci diff_comp_vs_late_uci diff_comp_vs_early diff_comp_vs_early_lci diff_comp_vs_early_uci diff_late_vs_early diff
> _late_vs_early_lci diff_late_vs_early_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt2, .10, .30) // tolerance of .06
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt2, .35, .65) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt2, .75, 1.25) // tolerance of .16
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt2, 2.80, 3.20) // tolerance of .40
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt2,  4.50, 5.50) // tolerance of .40
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as25m1 = (ests_diff_comp_vs_late , ests_diff_comp_vs_late_lci , ests_diff_comp_vs_late_uci ,  ///
>         ests_diff_comp_vs_early , ests_diff_comp_vs_early_lci, ests_diff_comp_vs_early_uci , ///
>         ests_diff_late_vs_early , ests_diff_late_vs_early_lci , ests_diff_late_vs_early_uci )

. matrix colnames est_as25m1 = Comp_Late Comp_Late_lci Comp_Late_uci Comp_Early Comp_Early_lci Comp_Early_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. *cap qui noi use "mariel_feb_23_2_early.dta", clear
. *qui ds
. *di word("`r(varlist)'", `c(k)')
. *browse 
. *NO EXTRAPOLA, REEMPLAZAR CON CERO EN UNA DE ESAS. NO EXTRAPOLA PORQUE LA PROBABILIDAD ES 1.
. 
. *cap qui noi use "mariel_feb_23_2_early_late.dta", clear
. *browse
. *NO HAY 6 MESES EN EARLY-LATE, SON SÓLO .78, que termina siendo absorvido por el año
. 
. esttab matrix(est_as25m1) using "${pathdata2}prob_prison_m1_IPW_diff.html", replace 
(output written to prob_prison_m1_IPW_diff.html)

Difference RMST

. cap qui noi use "mariel_feb_23_2_m1.dta", clear

. *estread using "mariel_feb_23_2.sters", replace
. 
. keep rmstdiff_comp_vs_late rmstdiff_comp_vs_late_lci rmstdiff_comp_vs_late_uci rmstdiff_comp_vs_early rmstdiff_comp_vs_early_lci rmstdiff_comp_vs_early_uci rmstdiff_late_vs_
> early rmstdiff_late_vs_early_lci rmstdiff_late_vs_early_uci tt2

. 
. foreach var of varlist rmstdiff_comp_vs_late rmstdiff_comp_vs_late_lci rmstdiff_comp_vs_late_uci rmstdiff_comp_vs_early rmstdiff_comp_vs_early_lci rmstdiff_comp_vs_early_uci
>  rmstdiff_late_vs_early rmstdiff_late_vs_early_lci rmstdiff_late_vs_early_uci {
  2.     local newname = substr("`var'", 5, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_comp_vs_late diff_comp_vs_late_lci diff_comp_vs_late_uci diff_comp_vs_early diff_comp_vs_early_lci diff_comp_vs_early_uci diff_late_vs_early diff
> _late_vs_early_lci diff_late_vs_early_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt2, .10, .30) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt2, .35, .65) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt2, .75, 1.25) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt2, 2.80, 3.20) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt2,  4.50, 5.50) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as26m1 = (ests_diff_comp_vs_early , ests_diff_comp_vs_early_lci, ests_diff_comp_vs_early_uci ,  ///
>         ests_diff_comp_vs_late , ests_diff_comp_vs_late_lci , ests_diff_comp_vs_late_uci , ///
>         ests_diff_late_vs_early , ests_diff_late_vs_early_lci , ests_diff_late_vs_early_uci )

. matrix colnames est_as26m1 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as26m1) using "${pathdata2}rmst_prison_m1_main_IPW_diff.html", replace 
(output written to rmst_prison_m1_main_IPW_diff.html)

#################################################_

#################################################_

Imprisonment_Imputed(2)_Main

#################################################_

Survival

. cap qui noi use "mariel_feb_23_2_m2.dta", clear

. 
. keep s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci tt

. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist s_tr_comp s_tr_comp_lci s_tr_comp_uci s_early_drop s_early_drop_lci s_early_drop_uci s_late_drop s_late_drop_lci s_late_drop_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as21m2 = (ests_s_tr_comp , ests_s_tr_comp_lci, ests_s_tr_comp_uci ,  ///
>         ests_s_early_drop , ests_s_early_drop_lci, ests_s_early_drop_uci , ///
>         ests_s_late_drop , ests_s_late_drop_lci , ests_s_late_drop_uci )

. matrix colnames est_as21m2 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as21m2) using "${pathdata2}prob_prison_m2_main.html", replace 
(output written to prob_prison_m2_main.html)

RMST

. cap qui noi use "mariel_feb_23_2_m2.dta", clear

. 
. keep rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci tt

. 
. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist rmst_h0 rmst_h0_lci rmst_h0_uci rmst_h1 rmst_h1_lci rmst_h1_uci rmst_h2 rmst_h2_lci rmst_h2_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.         }       

. 
. matrix est_as22m2 = (ests_rmst_h0 , ests_rmst_h0_lci , ests_rmst_h0_uci ,  ///
>         ests_rmst_h1 , ests_rmst_h1_lci , ests_rmst_h1_uci ,  ///
>         ests_rmst_h2 , ests_rmst_h2_lci , ests_rmst_h2_uci )

. matrix colnames est_as22m2 = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as22m2) using "${pathdata2}rmst_prison_m2_main.html", replace 
(output written to rmst_prison_m2_main.html)

Difference Survival

. cap qui noi use "mariel_feb_23_2_m2.dta", clear

. 
. keep sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_late_drop_uci sdif
> f_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci tt

. 
. foreach var of varlist sdiff_tr_comp_early_drop sdiff_tr_comp_early_drop_lci sdiff_tr_comp_early_drop_uci  sdiff_tr_comp_late_drop sdiff_tr_comp_late_drop_lci sdiff_tr_comp_
> late_drop_uci sdiff_early_late_drop sdiff_early_late_drop_lci sdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 2, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci  diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_d
> rop_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.001)*100,.1)                                    
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as23m2 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as23m2 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as23m2) using "${pathdata2}prob_prison_m2_main_diff.html", replace 
(output written to prob_prison_m2_main_diff.html)

Difference RMST

. cap qui noi use "mariel_feb_23_2_m2.dta", clear

. 
. keep rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci rmstdiff_tr_comp_l
> ate_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci tt

. 
. foreach var of varlist rmstdiff_tr_comp_early_drop rmstdiff_tr_comp_early_drop_lci rmstdiff_tr_comp_early_drop_uci rmstdiff_tr_comp_late_drop rmstdiff_tr_comp_late_drop_lci 
> rmstdiff_tr_comp_late_drop_uci rmstdiff_early_late_drop rmstdiff_early_late_drop_lci rmstdiff_early_late_drop_uci {
  2.     local newname = substr("`var'", 5, 50)
  3.     rename `var' `newname'
  4. }

. 
. foreach var of varlist diff_tr_comp_early_drop diff_tr_comp_early_drop_lci diff_tr_comp_early_drop_uci diff_tr_comp_late_drop diff_tr_comp_late_drop_lci diff_tr_comp_late_dr
> op_uci diff_early_late_drop diff_early_late_drop_lci diff_early_late_drop_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(tt, .24, .26) // tolerance of .02
  4.                                         scalar e3m_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(tt, .45, .55) // tolerance of .10
  6.                                         scalar e6m_`var' = round(round(r(mean),.0001),.001)                                     
  7.                                         qui summarize `var' if inrange(tt, .95, 1.05) // tolerance of .10
  8.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  9.                                         qui summarize `var' if inrange(tt, 2.85, 3.15) // tolerance of .30
 10.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
 11.                                         qui summarize `var' if inrange(tt,  4.85, 5.15) // tolerance of .30
 12.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
 13.          cap noi matrix ests_`var' = (`=scalar(e3m_`var')'\  `=scalar(e6m_`var')'\ `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 14.          matrix colnames ests_`var' = `var'
 15.          matrix rownames ests_`var' = 3_mths 6_mths 1_yr 3_yrs 5_yrs
 16.                 }

.         
. matrix est_as24m2 = (ests_diff_tr_comp_early_drop , ests_diff_tr_comp_early_drop_lci , ests_diff_tr_comp_early_drop_uci ,  ///
>         ests_diff_tr_comp_late_drop , ests_diff_tr_comp_late_drop_lci, ests_diff_tr_comp_late_drop_uci , ///
>         ests_diff_early_late_drop , ests_diff_early_late_drop_lci , ests_diff_early_late_drop_uci )

. matrix colnames est_as24m2 = Comp_Early Comp_Early_lci Comp_Early_uci Comp_Late Comp_Late_lci Comp_Late_uci Early_Late Early_Late_lci Early_Late_uci 

. 
. esttab matrix(est_as24m2) using "${pathdata2}rmst_prison_m2_main_diff.html", replace 
(output written to rmst_prison_m2_main_diff.html)

#################################################_

#################################################_

E-values, main analyses

#################################################_

#################################################_

Condemnatory Sentence, Listwise

. cap qui noi clear all

. qui estread using "mariel_feb_23.sters"

. 
. estimates replay m_nostag_rp6_tvc_1, eform

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Model m_nostag_rp6_tvc_1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Log likelihood = -54443.187                     Number of obs     =     60,253

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |   1.728953   .0499925    18.94   0.000     1.633694    1.829766
         mot_egr_late |   1.577917   .0370653    19.42   0.000     1.506917    1.652262
              tr_mod2 |   1.218636   .0262221     9.19   0.000      1.16831    1.271129
             sex_dum2 |   .7600293    .016327   -12.77   0.000     .7286932    .7927129
        edad_ini_cons |   .9868996   .0019513    -6.67   0.000     .9830825    .9907315
                 esc1 |   1.128982   .0298192     4.59   0.000     1.072025    1.188966
                 esc2 |   1.088746    .025948     3.57   0.000     1.039058     1.14081
            sus_prin2 |   1.066729   .0297425     2.32   0.021     1.009999    1.126646
            sus_prin3 |   1.392948   .0326517    14.14   0.000       1.3304    1.458437
            sus_prin4 |   1.076603   .0378667     2.10   0.036     1.004886    1.153438
            sus_prin5 |   1.141834   .0825502     1.83   0.067     .9909792    1.315654
    fr_cons_sus_prin2 |    .920203   .0450222    -1.70   0.089     .8360601    1.012814
    fr_cons_sus_prin3 |   .9969857   .0395705    -0.08   0.939     .9223689    1.077639
    fr_cons_sus_prin4 |   1.008748   .0420384     0.21   0.834     .9296295      1.0946
    fr_cons_sus_prin5 |   1.030657   .0409393     0.76   0.447     .9534613    1.114103
            cond_ocu2 |   1.017891   .0318157     0.57   0.570     .9574048    1.082198
            cond_ocu3 |   1.005554   .1418086     0.04   0.969     .7627188    1.325704
            cond_ocu4 |   1.104285   .0399243     2.74   0.006     1.028743    1.185375
            cond_ocu5 |   1.161881    .089036     1.96   0.050     .9998462    1.350175
            cond_ocu6 |   1.131352   .0207262     6.74   0.000      1.09145    1.172713
          policonsumo |   1.026642   .0224184     1.20   0.229     .9836297    1.071535
             num_hij2 |   1.165174   .0227514     7.83   0.000     1.121424     1.21063
              tenviv1 |   1.152096    .075424     2.16   0.031     1.013358    1.309827
              tenviv2 |   1.127523   .0494075     2.74   0.006     1.034728     1.22864
              tenviv4 |   1.037621   .0237463     1.61   0.107     .9921074    1.085222
              tenviv5 |   1.003652   .0179934     0.20   0.839     .9689976    1.039545
               mzone2 |   1.302629   .0273768    12.58   0.000     1.250061    1.357407
               mzone3 |   1.464532   .0421233    13.27   0.000     1.384256    1.549464
            n_off_vio |   1.355274   .0258706    15.93   0.000     1.305506     1.40694
            n_off_acq |   1.814333   .0324517    33.31   0.000     1.751831    1.879065
            n_off_sud |   1.256841   .0233136    12.32   0.000     1.211967    1.303375
            n_off_oth |   1.360377   .0257473    16.26   0.000     1.310838    1.411788
             psy_com2 |    1.07078   .0257019     2.85   0.004     1.021572    1.122359
             psy_com3 |    1.05835   .0187998     3.19   0.001     1.022137    1.095846
                 dep2 |   1.019981   .0195475     1.03   0.302     .9823791    1.059022
               rural2 |   1.028789   .0287124     1.02   0.309     .9740256    1.086632
               rural3 |   1.054563   .0324416     1.73   0.084     .9928578    1.120104
            porc_pobr |   1.228279   .1453468     1.74   0.082      .974027    1.548898
              susini2 |   1.095891   .0455133     2.20   0.027      1.01022    1.188826
              susini3 |   1.122648   .0372602     3.49   0.000     1.051944    1.198104
              susini4 |   1.082362   .0193437     4.43   0.000     1.045105    1.120947
              susini5 |   1.129855    .056192     2.45   0.014     1.024918    1.245535
         ano_nac_corr |    .874961    .003746   -31.20   0.000     .8676497    .8823339
               cohab2 |   .9707827   .0310641    -0.93   0.354     .9117682    1.033617
               cohab3 |   .9914812   .0390175    -0.22   0.828      .917883    1.070981
               cohab4 |   .9524348   .0296215    -1.57   0.117     .8961117    1.012298
             fis_com2 |   1.027195   .0166785     1.65   0.098     .9950202     1.06041
             fis_com3 |   .9022046   .0336831    -2.76   0.006     .8385445    .9706976
                rc_x1 |   .8517336   .0048089   -28.42   0.000     .8423604    .8612112
                rc_x2 |   1.028766   .0186435     1.56   0.118      .992867    1.065963
                rc_x3 |   .8953119   .0414545    -2.39   0.017     .8176403    .9803619
                _rcs1 |   2.632098   .0397141    64.14   0.000     2.555399    2.711098
                _rcs2 |   1.104931   .0062859    17.54   0.000     1.092679     1.11732
                _rcs3 |   1.042542   .0040782    10.65   0.000      1.03458    1.050566
                _rcs4 |   1.020136   .0025116     8.10   0.000     1.015225    1.025071
                _rcs5 |   1.011801   .0017195     6.90   0.000     1.008437    1.015177
                _rcs6 |   1.006751    .001313     5.16   0.000     1.004181    1.009328
  _rcs_mot_egr_early1 |     .90547    .016121    -5.58   0.000     .8744183    .9376243
   _rcs_mot_egr_late1 |   .9427967   .0154771    -3.59   0.000     .9129449    .9736246
                _cons |   2.9e+115   2.5e+116    30.83   0.000     1.3e+108    6.4e+122
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. scalar HR_early = r(table)["b",1]

. scalar HR_early_lo = r(table)["ll",1]

. scalar HR_early_up = r(table)["ul",1]

. scalar HR_late = r(table)["b",2]

. scalar HR_late_lo = r(table)["ll",2]

. scalar HR_late_up = r(table)["ul",2]

. 
. set scheme s1mono

. 
. di  "`=scalar(round(HR_early,.01))'  (95%CI `=scalar(round(HR_early_lo),.01)', `=round(scalar(HR_early_up),.01)')"
1.73  (95%CI 1.63, 1.83)

. 
. evalue hr `=scalar(HR_early)' , lcl(`=scalar(HR_early_lo)') ucl(`=scalar(HR_early_up)') true(1) common figure
   E-value (point estimate): 2.279
   E-value (CI): 2.157

. di  "`=scalar(round(HR_late,.01))'  (95%CI `=scalar(round(HR_late_lo),.01)', `=round(scalar(HR_late_up),.01)')"
1.58  (95%CI 1.51, 1.65)

. 
. evalue hr `=scalar(HR_late)' , lcl(`=scalar(HR_late_lo)') ucl(`=scalar(HR_late_up)') true(1) common figure
   E-value (point estimate): 2.084
   E-value (CI): 1.988

Imprisonment, Listwise

. cap qui noi clear all

. qui estread using "mariel_feb_23_2.sters"

. 
. estimates replay m_nostag_rp6_tvc_1, eform

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Model m_nostag_rp6_tvc_1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Log likelihood = -16977.437                     Number of obs     =     60,253

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |   2.012536     .12695    11.09   0.000     1.778485    2.277389
         mot_egr_late |   1.694464   .0920751     9.71   0.000     1.523278    1.884888
              tr_mod2 |   1.218438   .0518245     4.65   0.000     1.120982    1.324366
             sex_dum2 |    .607298   .0295195   -10.26   0.000     .5521115    .6680008
        edad_ini_cons |   .9714319   .0047127    -5.97   0.000     .9622389    .9807126
                 esc1 |   1.430409   .0886472     5.78   0.000     1.266802    1.615147
                 esc2 |   1.264154    .073243     4.05   0.000     1.128451    1.416176
            sus_prin2 |   1.157338   .0782559     2.16   0.031     1.013688    1.321344
            sus_prin3 |   1.681938   .0916982     9.54   0.000     1.511482    1.871617
            sus_prin4 |    1.17118   .0933799     1.98   0.048     1.001743    1.369277
            sus_prin5 |   1.590815   .2391632     3.09   0.002     1.184813    2.135941
    fr_cons_sus_prin2 |    .967409   .1088579    -0.29   0.768     .7759406    1.206124
    fr_cons_sus_prin3 |   .9785847   .0894334    -0.24   0.813     .8181005    1.170551
    fr_cons_sus_prin4 |   1.003281   .0951204     0.03   0.972     .8331449    1.208159
    fr_cons_sus_prin5 |   1.030036   .0934609     0.33   0.744     .8622201    1.230514
            cond_ocu2 |   1.048814   .0745353     0.67   0.502     .9124447    1.205563
            cond_ocu3 |   1.146648   .3093534     0.51   0.612     .6757487    1.945697
            cond_ocu4 |   1.220389   .0890058     2.73   0.006     1.057835    1.407921
            cond_ocu5 |   1.057984   .1641719     0.36   0.716     .7805393    1.434048
            cond_ocu6 |   1.189485   .0465057     4.44   0.000     1.101741    1.284218
          policonsumo |   .9915966   .0486117    -0.17   0.863     .9007536    1.091601
             num_hij2 |   1.125554   .0447828     2.97   0.003     1.041117     1.21684
              tenviv1 |   1.067279   .1350448     0.51   0.607     .8328636    1.367672
              tenviv2 |   1.125202   .0969405     1.37   0.171     .9503774    1.332185
              tenviv4 |   1.038047   .0510085     0.76   0.447     .9427354    1.142994
              tenviv5 |   1.010717   .0383263     0.28   0.779     .9383225    1.088697
               mzone2 |   1.450399   .0608534     8.86   0.000     1.335901    1.574711
               mzone3 |   1.528535   .0965347     6.72   0.000     1.350572    1.729948
            n_off_vio |   1.466613   .0554377    10.13   0.000     1.361884    1.579395
            n_off_acq |   2.798335   .0972513    29.61   0.000     2.614073    2.995586
            n_off_sud |   1.390646   .0507004     9.05   0.000     1.294743    1.493654
            n_off_oth |   1.736015   .0634121    15.10   0.000     1.616074    1.864858
             psy_com2 |   1.118023   .0550376     2.27   0.023     1.015191     1.23127
             psy_com3 |   1.100216   .0424081     2.48   0.013      1.02016    1.186555
                 dep2 |   1.036419   .0441269     0.84   0.401     .9534424    1.126617
               rural2 |    .898513   .0559683    -1.72   0.086      .795249    1.015186
               rural3 |   .8606054   .0595695    -2.17   0.030     .7514247    .9856499
            porc_pobr |   1.571197   .3932657     1.81   0.071      .962005     2.56616
              susini2 |   1.188536   .1083406     1.89   0.058     .9940805    1.421031
              susini3 |   1.270308   .0818754     3.71   0.000     1.119558    1.441358
              susini4 |    1.18061   .0440211     4.45   0.000     1.097408    1.270121
              susini5 |   1.421915   .1320064     3.79   0.000     1.185361    1.705677
         ano_nac_corr |   .8500967   .0080232   -17.21   0.000     .8345161    .8659682
               cohab2 |   .8802602   .0591132    -1.90   0.058     .7717015     1.00409
               cohab3 |   1.075106   .0859654     0.91   0.365     .9191564    1.257516
               cohab4 |    .964041   .0641775    -0.55   0.582      .846116    1.098401
             fis_com2 |   1.057973   .0364668     1.63   0.102     .9888599    1.131916
             fis_com3 |   .8191694   .0709746    -2.30   0.021     .6912319    .9707863
                rc_x1 |   .8503726   .0101848   -13.53   0.000     .8306432    .8705706
                rc_x2 |   .8817405   .0351634    -3.16   0.002      .815446    .9534245
                rc_x3 |   1.277763   .1359053     2.30   0.021     1.037326    1.573931
                _rcs1 |   2.200956   .0694371    25.01   0.000     2.068984    2.341346
                _rcs2 |   1.065717   .0083576     8.12   0.000     1.049462    1.082225
                _rcs3 |   1.033663    .006363     5.38   0.000     1.021266     1.04621
                _rcs4 |   1.017806   .0044294     4.06   0.000     1.009161    1.026524
                _rcs5 |   1.010267   .0032115     3.21   0.001     1.003993    1.016581
                _rcs6 |   1.008379   .0025225     3.34   0.001     1.003447    1.013335
  _rcs_mot_egr_early1 |   .8926688   .0314254    -3.23   0.001     .8331531    .9564359
   _rcs_mot_egr_late1 |   .9136598   .0309637    -2.66   0.008     .8549437    .9764086
                _cons |   1.4e+139   2.7e+140    16.86   0.000     9.7e+122    2.2e+155
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. scalar HR_early2 = r(table)["b",1]

. scalar HR_early_lo2 = r(table)["ll",1]

. scalar HR_early_up2 = r(table)["ul",1]

. scalar HR_late2 = r(table)["b",2]

. scalar HR_late_lo2 = r(table)["ll",2]

. scalar HR_late_up2 = r(table)["ul",2]

. 
. set scheme s1mono

. 
. di  "`=scalar(round(HR_early2,.01))'  (95%CI `=scalar(round(HR_early_lo2),.01)', `=round(scalar(HR_early_up2),.01)')"
2.01  (95%CI 1.78, 2.28)

. 
. evalue hr `=scalar(HR_early2)' , lcl(`=scalar(HR_early_lo2)') ucl(`=scalar(HR_early_up2)') true(1) figure
   E-value (point estimate): 3.440
   E-value (CI): 2.955

. di  "`=scalar(round(HR_late2,.01))'  (95%CI `=scalar(round(HR_late_lo2),.01)', `=round(scalar(HR_late_up2),.01)')"
1.69  (95%CI 1.52, 1.88)

. 
. evalue hr `=scalar(HR_late2)' , lcl(`=scalar(HR_late_lo2)') ucl(`=scalar(HR_late_up2)') true(1) figure
   E-value (point estimate): 2.779
   E-value (CI): 2.416

Condemnatory Sentence, Imputed

. cap qui noi clear all

. qui estread using "mariel_feb_23_m1.sters"

. 
. estimates replay m_nostag_rp8_tvc_1, eform

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Model m_nostag_rp8_tvc_1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Log likelihood = -67533.174                     Number of obs     =     70,863

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |    1.74308   .0445435    21.74   0.000     1.657926    1.832607
         mot_egr_late |   1.583146   .0330746    21.99   0.000      1.51963    1.649317
              tr_mod2 |   1.217761       .023    10.43   0.000     1.173506    1.263685
             sex_dum2 |     .73504   .0141646   -15.97   0.000     .7077957     .763333
        edad_ini_cons |   .9880599   .0016926    -7.01   0.000     .9847481    .9913828
                 esc1 |   1.157902    .027096     6.27   0.000     1.105995    1.212246
                 esc2 |   1.106586   .0234376     4.78   0.000      1.06159     1.15349
            sus_prin2 |   1.071889   .0264682     2.81   0.005     1.021248    1.125042
            sus_prin3 |    1.40807   .0292356    16.48   0.000     1.351919    1.466553
            sus_prin4 |   1.040355   .0321132     1.28   0.200     .9792802    1.105238
            sus_prin5 |   1.014537   .0647975     0.23   0.821     .8951642    1.149829
    fr_cons_sus_prin2 |   .9349407    .040723    -1.54   0.122     .8584371    1.018262
    fr_cons_sus_prin3 |   1.008606   .0356281     0.24   0.808     .9411391     1.08091
    fr_cons_sus_prin4 |   1.032608   .0382571     0.87   0.386     .9602832     1.11038
    fr_cons_sus_prin5 |   1.066898   .0376756     1.83   0.067      .995553    1.143357
            cond_ocu2 |   1.031147   .0286569     1.10   0.270     .9764829    1.088871
            cond_ocu3 |   .9603183   .1248672    -0.31   0.755     .7442796    1.239066
            cond_ocu4 |   1.118921    .036866     3.41   0.001     1.048948    1.193561
            cond_ocu5 |   1.256781   .0704571     4.08   0.000     1.126004    1.402747
            cond_ocu6 |   1.160912   .0190489     9.09   0.000     1.124171    1.198854
          policonsumo |   1.033559   .0201903     1.69   0.091     .9947347    1.073899
             num_hij2 |   1.156898   .0199633     8.45   0.000     1.118425    1.196694
              tenviv1 |   1.082366   .0649739     1.32   0.187     .9622259    1.217507
              tenviv2 |   1.088573   .0419101     2.20   0.027     1.009454    1.173894
              tenviv4 |   1.053361   .0207758     2.64   0.008     1.013418    1.094878
              tenviv5 |   1.010574   .0162738     0.65   0.514     .9791761    1.042979
               mzone2 |   1.286188   .0240552    13.46   0.000     1.239895     1.33421
               mzone3 |   1.428232   .0375361    13.56   0.000     1.356525    1.503729
            n_off_vio |   1.355585   .0239751    17.20   0.000       1.3094    1.403399
            n_off_acq |   1.809644    .029703    36.14   0.000     1.752354    1.868807
            n_off_sud |    1.24879   .0214402    12.94   0.000     1.207467    1.291527
            n_off_oth |   1.352543   .0236902    17.24   0.000     1.306899    1.399781
             psy_com2 |   1.058857   .0224264     2.70   0.007     1.015802    1.103737
             psy_com3 |   1.043868    .016503     2.72   0.007     1.012019     1.07672
                 dep2 |   1.014576   .0174076     0.84   0.399     .9810246    1.049274
               rural2 |   1.022953   .0262479     0.88   0.376     .9727802    1.075713
               rural3 |   1.043664   .0294606     1.51   0.130     .9874909    1.103033
            porc_pobr |    1.29553   .1346303     2.49   0.013     1.056796    1.588194
              susini2 |   1.049822   .0312983     1.63   0.103     .9902367    1.112993
              susini3 |    1.14337   .0346017     4.43   0.000     1.077524     1.21324
              susini4 |   1.087998   .0175085     5.24   0.000     1.054217    1.122861
              susini5 |   1.141778   .0524973     2.88   0.004     1.043385     1.24945
         ano_nac_corr |   .8805033   .0031795   -35.24   0.000     .8742935    .8867572
               cohab2 |   .9385429   .0252554    -2.36   0.018      .890326    .9893711
               cohab3 |   .9807871   .0319577    -0.60   0.552     .9201093    1.045466
               cohab4 |     .92591   .0244015    -2.92   0.003     .8792982    .9749927
             fis_com2 |   1.025914   .0148909     1.76   0.078     .9971396    1.055519
             fis_com3 |   .8874548   .0293626    -3.61   0.000     .8317314    .9469115
                rc_x1 |    .861173   .0041794   -30.80   0.000     .8530203    .8694037
                rc_x2 |    1.00745   .0162096     0.46   0.645     .9761755    1.039727
                rc_x3 |    .940499   .0387113    -1.49   0.136     .8676061    1.019516
                _rcs1 |   2.660683    .035516    73.31   0.000     2.591976    2.731212
                _rcs2 |   1.112745    .005837    20.37   0.000     1.101363    1.124244
                _rcs3 |   1.048789   .0038702    12.91   0.000     1.041231    1.056402
                _rcs4 |   1.023992   .0024089    10.08   0.000     1.019281    1.028724
                _rcs5 |   1.014865   .0016172     9.26   0.000     1.011701     1.01804
                _rcs6 |   1.011019   .0012537     8.84   0.000     1.008565    1.013479
                _rcs7 |   1.007845   .0010726     7.34   0.000     1.005745    1.009949
                _rcs8 |   1.004567    .000909     5.04   0.000     1.002787     1.00635
  _rcs_mot_egr_early1 |    .907554   .0143523    -6.13   0.000     .8798554    .9361246
   _rcs_mot_egr_late1 |   .9431117   .0136921    -4.03   0.000     .9166539    .9703331
                _cons |   7.9e+109   5.7e+110    34.81   0.000     5.1e+103    1.2e+116
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. scalar HR_earlym1 = r(table)["b",1]

. scalar HR_early_lom1 = r(table)["ll",1]

. scalar HR_early_upm1 = r(table)["ul",1]

. scalar HR_latem1 = r(table)["b",2]

. scalar HR_late_lom1 = r(table)["ll",2]

. scalar HR_late_upm1 = r(table)["ul",2]

. 
. set scheme s1mono

. 
. di  "`=scalar(round(HR_earlym1,.01))'  (95%CI `=scalar(round(HR_early_lom1),.01)', `=round(scalar(HR_early_upm1),.01)')"
1.74  (95%CI 1.66, 1.83)

. 
. evalue hr `=scalar(HR_earlym1)' , lcl(`=scalar(HR_early_lom1)') ucl(`=scalar(HR_early_upm1)') true(1) common figure
   E-value (point estimate): 2.297
   E-value (CI): 2.188

. 

. di  "`=scalar(round(HR_latem1,.01))'  (95%CI `=scalar(round(HR_late_lom1),.01)', `=round(scalar(HR_late_upm1),.01)')"
1.58  (95%CI 1.52, 1.65)

. 
. evalue hr `=scalar(HR_latem1)' , lcl(`=scalar(HR_late_lom1)') ucl(`=scalar(HR_late_upm1)') true(1) common figure
   E-value (point estimate): 2.091
   E-value (CI): 2.005

Imprisonment, Imputed

. cap qui noi clear all

. qui estread using "mariel_feb_23_2_m1.sters"

. 
. estimates replay m_nostag_rp6_tvc_1, eform

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Model m_nostag_rp6_tvc_1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Log likelihood = -21759.872                     Number of obs     =     70,863

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |   1.994852   .1087314    12.67   0.000     1.792731    2.219761
         mot_egr_late |   1.651233   .0777884    10.65   0.000     1.505598    1.810956
              tr_mod2 |   1.152116   .0429533     3.80   0.000     1.070932    1.239455
             sex_dum2 |   .5924607   .0255581   -12.13   0.000      .544427    .6447322
        edad_ini_cons |   .9734059   .0040331    -6.51   0.000     .9655331    .9813429
                 esc1 |   1.516986   .0833309     7.59   0.000     1.362145    1.689428
                 esc2 |   1.344025     .06934     5.73   0.000     1.214766    1.487037
            sus_prin2 |   1.195219   .0708791     3.01   0.003     1.064068    1.342535
            sus_prin3 |   1.716276   .0822599    11.27   0.000      1.56239    1.885318
            sus_prin4 |   1.142999   .0793454     1.93   0.054     .9975999    1.309589
            sus_prin5 |   1.354906   .1839488     2.24   0.025     1.038354     1.76796
    fr_cons_sus_prin2 |    .977386   .0969542    -0.23   0.818     .8046908    1.187143
    fr_cons_sus_prin3 |   .9957392   .0799293    -0.05   0.958     .8507824    1.165394
    fr_cons_sus_prin4 |   1.038108    .086308     0.45   0.653      .882011    1.221831
    fr_cons_sus_prin5 |    1.08905   .0865887     1.07   0.283     .9319019    1.272699
            cond_ocu2 |   1.087743   .0670889     1.36   0.173     .9638878    1.227513
            cond_ocu3 |   1.143944   .2800258     0.55   0.583       .70801     1.84829
            cond_ocu4 |   1.240744   .0810192     3.30   0.001     1.091691    1.410148
            cond_ocu5 |   1.332646   .1368113     2.80   0.005     1.089756    1.629673
            cond_ocu6 |   1.211739   .0420048     5.54   0.000     1.132146    1.296928
          policonsumo |   1.007253   .0431286     0.17   0.866     .9261719    1.095431
             num_hij2 |   1.136224   .0394231     3.68   0.000     1.061525     1.21618
              tenviv1 |   1.018513   .1150669     0.16   0.871     .8162099    1.270959
              tenviv2 |   1.068074   .0802883     0.88   0.381     .9217552     1.23762
              tenviv4 |   1.012196   .0420598     0.29   0.770      .933028    1.098082
              tenviv5 |   .9928354   .0331953    -0.22   0.830     .9298599    1.060076
               mzone2 |   1.416263   .0524875     9.39   0.000     1.317037    1.522965
               mzone3 |   1.544621   .0865199     7.76   0.000     1.384022    1.723855
            n_off_vio |   1.461835   .0503418    11.03   0.000     1.366423    1.563909
            n_off_acq |   2.796745   .0871343    33.01   0.000     2.631075    2.972847
            n_off_sud |   1.376993   .0456524     9.65   0.000     1.290361    1.469441
            n_off_oth |   1.702386   .0564758    16.04   0.000     1.595218    1.816754
             psy_com2 |   1.048481   .0402961     1.23   0.218     .9724036    1.130511
                 dep2 |   1.032711   .0387488     0.86   0.391     .9594905     1.11152
               rural2 |   .9370524   .0520279    -1.17   0.242     .8404322    1.044781
               rural3 |   .8649187    .054017    -2.32   0.020     .7652705    .9775424
            porc_pobr |   1.709119   .3691358     2.48   0.013     1.119256    2.609846
              susini2 |   1.097617   .0720002     1.42   0.156     .9651941    1.248208
              susini3 |   1.271345   .0731854     4.17   0.000     1.135701    1.423191
              susini4 |    1.15569   .0379013     4.41   0.000     1.083742    1.232415
              susini5 |   1.378443   .1164494     3.80   0.000       1.1681    1.626662
         ano_nac_corr |   .8465336   .0067735   -20.82   0.000     .8333613     .859914
               cohab2 |   .8633277   .0473393    -2.68   0.007     .7753563    .9612803
               cohab3 |    1.07592   .0686957     1.15   0.252     .9493631    1.219349
               cohab4 |   .9448006   .0518821    -1.03   0.301     .8483947    1.052162
             fis_com2 |   1.112992   .0326294     3.65   0.000     1.050843    1.178818
                rc_x1 |   .8447476   .0086673   -16.44   0.000     .8279298    .8619071
                rc_x2 |   .8807967   .0305094    -3.66   0.000      .822984    .9426706
                rc_x3 |   1.297611   .1196287     2.83   0.005     1.083106    1.554598
                _rcs1 |   2.177066   .0586595    28.87   0.000     2.065078    2.295126
                _rcs2 |   1.071884   .0075279     9.88   0.000     1.057231    1.086741
                _rcs3 |   1.033961   .0056547     6.11   0.000     1.022937    1.045104
                _rcs4 |   1.019485   .0038677     5.09   0.000     1.011932    1.027094
                _rcs5 |   1.012627   .0028211     4.50   0.000     1.007113    1.018171
                _rcs6 |    1.01034   .0021956     4.73   0.000     1.006046    1.014653
  _rcs_mot_egr_early1 |   .8978523   .0271955    -3.56   0.000     .8461013    .9527685
   _rcs_mot_egr_late1 |   .9205885   .0267904    -2.84   0.004     .8695497     .974623
                _cons |   7.4e+142   1.2e+144    20.43   0.000     1.5e+129    3.7e+156
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. scalar HR_early2m1 = r(table)["b",1]

. scalar HR_early_lo2m1 = r(table)["ll",1]

. scalar HR_early_up2m1 = r(table)["ul",1]

. scalar HR_late2m1 = r(table)["b",2]

. scalar HR_late_lo2m1 = r(table)["ll",2]

. scalar HR_late_up2m1 = r(table)["ul",2]

. 
. set scheme s1mono

. 
. di  "`=scalar(round(HR_early2m1,.01))'  (95%CI `=scalar(round(HR_early_lo2m1),.01)', `=round(scalar(HR_early_up2m1),.01)')"
1.99  (95%CI 1.79, 2.22)

. 
. evalue hr `=scalar(HR_early2m1)' , lcl(`=scalar(HR_early_lo2m1)') ucl(`=scalar(HR_early_up2m1)') true(1) figure
   E-value (point estimate): 3.404
   E-value (CI): 2.985

. 

. di  "`=scalar(round(HR_late2m1,.01))'  (95%CI `=scalar(round(HR_late_lo2m1),.01)', `=round(scalar(HR_late_up2m1),.01)')"
1.65  (95%CI 1.51, 1.81)

. 
. evalue hr `=scalar(HR_late2m1)' , lcl(`=scalar(HR_late_lo2m1)') ucl(`=scalar(HR_late_up2m1)') true(1) figure
   E-value (point estimate): 2.688
   E-value (CI): 2.378

*#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#: *#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#: *#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:

Figure

. *C:\Users\CISS Fondecyt\Mi unidad\Alvacast\SISTRAT 2022 (github)
. graph use "_figs\h_m_ns_rp6_stdif_s2_m1.gph"
(note:  named style large not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)

. graph export "_figs/h_m_ns_rp6_stdif_s2_m1.pdf", as(pdf) name("h_m_ns_rp6_stdif_s2_m1") replace
(file _figs/h_m_ns_rp6_stdif_s2_m1.pdf written in PDF format)

. 
. graph use "_figs\h_m_ns_rp6_stdif_rmst_m1.gph" 
(note:  named style large not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)

. graph export "_figs/h_m_ns_rp6_stdif_rmst_m1.pdf", as(pdf) name("h_m_ns_rp6_stdif_rmst_m1") replace
(file _figs/h_m_ns_rp6_stdif_rmst_m1.pdf written in PDF format)

. 
. graph use "_figs\h_m_ns_rp6_stdif_s2_pris_m1.gph" 
(note:  named style large not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)

. graph export "_figs/h_m_ns_rp6_stdif_s2_pris_m1.pdf", as(pdf) name("h_m_ns_rp6_stdif_s2_pris_m1") replace
(file _figs/h_m_ns_rp6_stdif_s2_pris_m1.pdf written in PDF format)

. 
. graph use "_figs\h_m_ns_rp6_stdif_rmst_pris_m1.gph" 
(note:  named style large not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)

. graph export "_figs/h_m_ns_rp6_stdif_rmst_pris_m1.pdf", as(pdf) name("h_m_ns_rp6_stdif_rmst_pris_m1") replace
(file _figs/h_m_ns_rp6_stdif_rmst_pris_m1.pdf written in PDF format)

. 

HACER GRAFICO DE PROBABILIDADES Y RMSTS EN EL TIEMPO

. graph use "_figs\h_m_ns_rp6_s_m1.gph"
(note:  named style large not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)

. gr_edit .yaxis1.title.text = {}

. gr_edit .yaxis1.title.text.Arrpush `"Probibability of avoiding condemnatory sentence"'

. gr_edit .legend.plotregion1.key[1].view.style.editstyle line(color(%60)) editcopy

. gr_edit .legend.plotregion1.key[2].view.style.editstyle line(color(%60)) editcopy

. gr_edit .legend.plotregion1.key[3].view.style.editstyle line(color(%60)) editcopy

. graph export "_figs/h_m_ns_rp6_s_m1.pdf", as(pdf) name("h_m_ns_rp6_s_m1") replace
(file _figs/h_m_ns_rp6_s_m1.pdf written in PDF format)

. 
. 
. graph use "_figs\h_m_ns_rp6_s_pris_m1.gph"
(note:  named style large not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)

. gr_edit .yaxis1.title.text = {}

. gr_edit .yaxis1.title.text.Arrpush `"Probibability of avoiding imprisonment"'

. gr_edit .legend.plotregion1.key[1].view.style.editstyle line(color(%60)) editcopy

. gr_edit .legend.plotregion1.key[2].view.style.editstyle line(color(%60)) editcopy

. gr_edit .legend.plotregion1.key[3].view.style.editstyle line(color(%60)) editcopy

. graph export "_figs/h_m_ns_rp6_s_pris_m1.pdf", as(pdf) name("h_m_ns_rp6_s_pris_m1") replace
(file _figs/h_m_ns_rp6_s_pris_m1.pdf written in PDF format)

. 
. 

*#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#: *#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#: *#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:

Hazard tables

Condemnatory Sentence, Imputed

. cap qui noi clear all

. qui estread using "mariel_feb_23_m1.sters"

. estimates replay m_nostag_rp8_tvc_1, eform

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Model m_nostag_rp8_tvc_1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Log likelihood = -67533.174                     Number of obs     =     70,863

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |    1.74308   .0445435    21.74   0.000     1.657926    1.832607
         mot_egr_late |   1.583146   .0330746    21.99   0.000      1.51963    1.649317
              tr_mod2 |   1.217761       .023    10.43   0.000     1.173506    1.263685
             sex_dum2 |     .73504   .0141646   -15.97   0.000     .7077957     .763333
        edad_ini_cons |   .9880599   .0016926    -7.01   0.000     .9847481    .9913828
                 esc1 |   1.157902    .027096     6.27   0.000     1.105995    1.212246
                 esc2 |   1.106586   .0234376     4.78   0.000      1.06159     1.15349
            sus_prin2 |   1.071889   .0264682     2.81   0.005     1.021248    1.125042
            sus_prin3 |    1.40807   .0292356    16.48   0.000     1.351919    1.466553
            sus_prin4 |   1.040355   .0321132     1.28   0.200     .9792802    1.105238
            sus_prin5 |   1.014537   .0647975     0.23   0.821     .8951642    1.149829
    fr_cons_sus_prin2 |   .9349407    .040723    -1.54   0.122     .8584371    1.018262
    fr_cons_sus_prin3 |   1.008606   .0356281     0.24   0.808     .9411391     1.08091
    fr_cons_sus_prin4 |   1.032608   .0382571     0.87   0.386     .9602832     1.11038
    fr_cons_sus_prin5 |   1.066898   .0376756     1.83   0.067      .995553    1.143357
            cond_ocu2 |   1.031147   .0286569     1.10   0.270     .9764829    1.088871
            cond_ocu3 |   .9603183   .1248672    -0.31   0.755     .7442796    1.239066
            cond_ocu4 |   1.118921    .036866     3.41   0.001     1.048948    1.193561
            cond_ocu5 |   1.256781   .0704571     4.08   0.000     1.126004    1.402747
            cond_ocu6 |   1.160912   .0190489     9.09   0.000     1.124171    1.198854
          policonsumo |   1.033559   .0201903     1.69   0.091     .9947347    1.073899
             num_hij2 |   1.156898   .0199633     8.45   0.000     1.118425    1.196694
              tenviv1 |   1.082366   .0649739     1.32   0.187     .9622259    1.217507
              tenviv2 |   1.088573   .0419101     2.20   0.027     1.009454    1.173894
              tenviv4 |   1.053361   .0207758     2.64   0.008     1.013418    1.094878
              tenviv5 |   1.010574   .0162738     0.65   0.514     .9791761    1.042979
               mzone2 |   1.286188   .0240552    13.46   0.000     1.239895     1.33421
               mzone3 |   1.428232   .0375361    13.56   0.000     1.356525    1.503729
            n_off_vio |   1.355585   .0239751    17.20   0.000       1.3094    1.403399
            n_off_acq |   1.809644    .029703    36.14   0.000     1.752354    1.868807
            n_off_sud |    1.24879   .0214402    12.94   0.000     1.207467    1.291527
            n_off_oth |   1.352543   .0236902    17.24   0.000     1.306899    1.399781
             psy_com2 |   1.058857   .0224264     2.70   0.007     1.015802    1.103737
             psy_com3 |   1.043868    .016503     2.72   0.007     1.012019     1.07672
                 dep2 |   1.014576   .0174076     0.84   0.399     .9810246    1.049274
               rural2 |   1.022953   .0262479     0.88   0.376     .9727802    1.075713
               rural3 |   1.043664   .0294606     1.51   0.130     .9874909    1.103033
            porc_pobr |    1.29553   .1346303     2.49   0.013     1.056796    1.588194
              susini2 |   1.049822   .0312983     1.63   0.103     .9902367    1.112993
              susini3 |    1.14337   .0346017     4.43   0.000     1.077524     1.21324
              susini4 |   1.087998   .0175085     5.24   0.000     1.054217    1.122861
              susini5 |   1.141778   .0524973     2.88   0.004     1.043385     1.24945
         ano_nac_corr |   .8805033   .0031795   -35.24   0.000     .8742935    .8867572
               cohab2 |   .9385429   .0252554    -2.36   0.018      .890326    .9893711
               cohab3 |   .9807871   .0319577    -0.60   0.552     .9201093    1.045466
               cohab4 |     .92591   .0244015    -2.92   0.003     .8792982    .9749927
             fis_com2 |   1.025914   .0148909     1.76   0.078     .9971396    1.055519
             fis_com3 |   .8874548   .0293626    -3.61   0.000     .8317314    .9469115
                rc_x1 |    .861173   .0041794   -30.80   0.000     .8530203    .8694037
                rc_x2 |    1.00745   .0162096     0.46   0.645     .9761755    1.039727
                rc_x3 |    .940499   .0387113    -1.49   0.136     .8676061    1.019516
                _rcs1 |   2.660683    .035516    73.31   0.000     2.591976    2.731212
                _rcs2 |   1.112745    .005837    20.37   0.000     1.101363    1.124244
                _rcs3 |   1.048789   .0038702    12.91   0.000     1.041231    1.056402
                _rcs4 |   1.023992   .0024089    10.08   0.000     1.019281    1.028724
                _rcs5 |   1.014865   .0016172     9.26   0.000     1.011701     1.01804
                _rcs6 |   1.011019   .0012537     8.84   0.000     1.008565    1.013479
                _rcs7 |   1.007845   .0010726     7.34   0.000     1.005745    1.009949
                _rcs8 |   1.004567    .000909     5.04   0.000     1.002787     1.00635
  _rcs_mot_egr_early1 |    .907554   .0143523    -6.13   0.000     .8798554    .9361246
   _rcs_mot_egr_late1 |   .9431117   .0136921    -4.03   0.000     .9166539    .9703331
                _cons |   7.9e+109   5.7e+110    34.81   0.000     5.1e+103    1.2e+116
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. // sacar matrices
. matrix table_r = r(table)

. 
. // Column and rownames
. global rownms: rown r(table)

. di "$rownms"
b se z pvalue ll ul df crit eform

. global colnms: coln r(table)

. di "$colnms"
mot_egr_early mot_egr_late tr_mod2 sex_dum2 edad_ini_cons esc1 esc2 sus_prin2 sus_prin3 sus_prin4 sus_prin5 fr_cons_sus_prin2 fr_cons_sus_prin3 fr_cons_sus_prin4 fr_cons_sus_p
> rin5 cond_ocu2 cond_ocu3 cond_ocu4 cond_ocu5 cond_ocu6 policonsumo num_hij2 tenviv1 tenviv2 tenviv4 tenviv5 mzone2 mzone3 n_off_vio n_off_acq n_off_sud n_off_oth psy_com2 ps
> y_com3 dep2 rural2 rural3 porc_pobr susini2 susini3 susini4 susini5 ano_nac_corr cohab2 cohab3 cohab4 fis_com2 fis_com3 rc_x1 rc_x2 rc_x3 _rcs1 _rcs2 _rcs3 _rcs4 _rcs5 _rcs6
>  _rcs7 _rcs8 _rcs_mot_egr_early1 _rcs_mot_egr_late1 _cons _d_rcs1 _d_rcs2 _d_rcs3 _d_rcs4 _d_rcs5 _d_rcs6 _d_rcs7 _d_rcs8 _d_rcs_mot_egr_early1 _d_rcs_mot_egr_late1

. local reqs : roweq r(table) //coleq

. di "`reqs'"
_ _ _ _ _ _ _ _ _

. global ceqs : coleq r(table) //coleq

. di "`ceqs'"


. local cname : colfullnames r(table)

. di "`cname'"
xb:mot_egr_early xb:mot_egr_late xb:tr_mod2 xb:sex_dum2 xb:edad_ini_cons xb:esc1 xb:esc2 xb:sus_prin2 xb:sus_prin3 xb:sus_prin4 xb:sus_prin5 xb:fr_cons_sus_prin2 xb:fr_cons_su
> s_prin3 xb:fr_cons_sus_prin4 xb:fr_cons_sus_prin5 xb:cond_ocu2 xb:cond_ocu3 xb:cond_ocu4 xb:cond_ocu5 xb:cond_ocu6 xb:policonsumo xb:num_hij2 xb:tenviv1 xb:tenviv2 xb:tenviv
> 4 xb:tenviv5 xb:mzone2 xb:mzone3 xb:n_off_vio xb:n_off_acq xb:n_off_sud xb:n_off_oth xb:psy_com2 xb:psy_com3 xb:dep2 xb:rural2 xb:rural3 xb:porc_pobr xb:susini2 xb:susini3 x
> b:susini4 xb:susini5 xb:ano_nac_corr xb:cohab2 xb:cohab3 xb:cohab4 xb:fis_com2 xb:fis_com3 xb:rc_x1 xb:rc_x2 xb:rc_x3 xb:_rcs1 xb:_rcs2 xb:_rcs3 xb:_rcs4 xb:_rcs5 xb:_rcs6 x
> b:_rcs7 xb:_rcs8 xb:_rcs_mot_egr_early1 xb:_rcs_mot_egr_late1 xb:_cons dxb:_d_rcs1 dxb:_d_rcs2 dxb:_d_rcs3 dxb:_d_rcs4 dxb:_d_rcs5 dxb:_d_rcs6 dxb:_d_rcs7 dxb:_d_rcs8 dxb:_d
> _rcs_mot_egr_early1 dxb:_d_rcs_mot_egr_late1

. 
. // Eliminate equations
. matrix coleq table_r = ""

. 
. // Subset matrix by column names
. *https://www.stata.com/manuals13/u14.pdf
. *https://www.stata.com/manuals13/dfunctions.pdf#dfunctionsDescriptionMatrixfunctionsreturningamatrix
. *
. matrix A = table_r[1... , "mot_egr_early"], table_r[1... , "mot_egr_late"], table_r[1... , "_rcs1".." _rcs_mot_egr_late1"], table_r[1... , "_d_rcs1".." _d_rcs_mot_egr_late1"
> ]

. matrix mod1= A["b","mot_egr_early".."_d_rcs_mot_egr_late1"] \ A["ll","mot_egr_early".."_d_rcs_mot_egr_late1"] \ A["ul","mot_egr_early".."_d_rcs_mot_egr_early1"...] \ A["pval
> ue","mot_egr_early".."_d_rcs_mot_egr_early1"...]  // three dots, until the last

. 
. //make another matrix
. mat mod1b= mod1

. 
. //mata: mata drop st_trans_matrix()
. mata:
------------------------------------------------- mata (type end to exit) -----------------------------------------------------------------------------------------------------
: void st_transpose_matrix(string scalar matname)
> {
>     // Convert Stata matrix to Mata matrix
>     M = st_matrix(matname)
> 
>     // Transpose the matrix
>     transposed_M = M'
> 
>     // Convert Mata matrix to Stata matrix
>     st_matrix(matname, transposed_M)
> }

: end
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

. 
. //transpose function
. mata: st_transpose_matrix("mod1b")

. 
. //move colnames and rownames to transpose
. local cnames :  rownames mod1

. di " `cnames'"
 b ll ul pvalue

. mat colnames mod1b = `cnames'

. local rnames :  colnames mod1 

. mat rownames mod1b = `rnames' 

. 
. //export
. esttab matrix(mod1b) using "mat_tab1.html", replace
(output written to mat_tab1.html)

. 
. *interpreting this value directly can be misleading, because the "_rcs" term represents a change in the hazard ratio over time, and the exact shape of this change is determi
> ned by the restricted cubic spline function used in the model.
. *the most effective way to interpret the "_rcs" term is to visualize the hazard ratio over time.¨
. *hazard ratio starts at 1.74308 (the main effect) at time zero and then changes over time according to the .907554 "_rcs" term. The trajectory of the hazard ratio will likel
> y be decreasing over time, 
. *direct interpretation of the "_rcs" term is not as straightforward. 
. *The most effective way to understand the combined effect of the main effect and the "_rcs" term is to visualize the hazard ratio over time. 

Imprisonment, Imputed

. cap qui noi clear all

. qui estread using "mariel_feb_23_2_m1.sters"

. estimates replay m_nostag_rp6_tvc_1, eform

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Model m_nostag_rp6_tvc_1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Log likelihood = -21759.872                     Number of obs     =     70,863

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |   1.994852   .1087314    12.67   0.000     1.792731    2.219761
         mot_egr_late |   1.651233   .0777884    10.65   0.000     1.505598    1.810956
              tr_mod2 |   1.152116   .0429533     3.80   0.000     1.070932    1.239455
             sex_dum2 |   .5924607   .0255581   -12.13   0.000      .544427    .6447322
        edad_ini_cons |   .9734059   .0040331    -6.51   0.000     .9655331    .9813429
                 esc1 |   1.516986   .0833309     7.59   0.000     1.362145    1.689428
                 esc2 |   1.344025     .06934     5.73   0.000     1.214766    1.487037
            sus_prin2 |   1.195219   .0708791     3.01   0.003     1.064068    1.342535
            sus_prin3 |   1.716276   .0822599    11.27   0.000      1.56239    1.885318
            sus_prin4 |   1.142999   .0793454     1.93   0.054     .9975999    1.309589
            sus_prin5 |   1.354906   .1839488     2.24   0.025     1.038354     1.76796
    fr_cons_sus_prin2 |    .977386   .0969542    -0.23   0.818     .8046908    1.187143
    fr_cons_sus_prin3 |   .9957392   .0799293    -0.05   0.958     .8507824    1.165394
    fr_cons_sus_prin4 |   1.038108    .086308     0.45   0.653      .882011    1.221831
    fr_cons_sus_prin5 |    1.08905   .0865887     1.07   0.283     .9319019    1.272699
            cond_ocu2 |   1.087743   .0670889     1.36   0.173     .9638878    1.227513
            cond_ocu3 |   1.143944   .2800258     0.55   0.583       .70801     1.84829
            cond_ocu4 |   1.240744   .0810192     3.30   0.001     1.091691    1.410148
            cond_ocu5 |   1.332646   .1368113     2.80   0.005     1.089756    1.629673
            cond_ocu6 |   1.211739   .0420048     5.54   0.000     1.132146    1.296928
          policonsumo |   1.007253   .0431286     0.17   0.866     .9261719    1.095431
             num_hij2 |   1.136224   .0394231     3.68   0.000     1.061525     1.21618
              tenviv1 |   1.018513   .1150669     0.16   0.871     .8162099    1.270959
              tenviv2 |   1.068074   .0802883     0.88   0.381     .9217552     1.23762
              tenviv4 |   1.012196   .0420598     0.29   0.770      .933028    1.098082
              tenviv5 |   .9928354   .0331953    -0.22   0.830     .9298599    1.060076
               mzone2 |   1.416263   .0524875     9.39   0.000     1.317037    1.522965
               mzone3 |   1.544621   .0865199     7.76   0.000     1.384022    1.723855
            n_off_vio |   1.461835   .0503418    11.03   0.000     1.366423    1.563909
            n_off_acq |   2.796745   .0871343    33.01   0.000     2.631075    2.972847
            n_off_sud |   1.376993   .0456524     9.65   0.000     1.290361    1.469441
            n_off_oth |   1.702386   .0564758    16.04   0.000     1.595218    1.816754
             psy_com2 |   1.048481   .0402961     1.23   0.218     .9724036    1.130511
                 dep2 |   1.032711   .0387488     0.86   0.391     .9594905     1.11152
               rural2 |   .9370524   .0520279    -1.17   0.242     .8404322    1.044781
               rural3 |   .8649187    .054017    -2.32   0.020     .7652705    .9775424
            porc_pobr |   1.709119   .3691358     2.48   0.013     1.119256    2.609846
              susini2 |   1.097617   .0720002     1.42   0.156     .9651941    1.248208
              susini3 |   1.271345   .0731854     4.17   0.000     1.135701    1.423191
              susini4 |    1.15569   .0379013     4.41   0.000     1.083742    1.232415
              susini5 |   1.378443   .1164494     3.80   0.000       1.1681    1.626662
         ano_nac_corr |   .8465336   .0067735   -20.82   0.000     .8333613     .859914
               cohab2 |   .8633277   .0473393    -2.68   0.007     .7753563    .9612803
               cohab3 |    1.07592   .0686957     1.15   0.252     .9493631    1.219349
               cohab4 |   .9448006   .0518821    -1.03   0.301     .8483947    1.052162
             fis_com2 |   1.112992   .0326294     3.65   0.000     1.050843    1.178818
                rc_x1 |   .8447476   .0086673   -16.44   0.000     .8279298    .8619071
                rc_x2 |   .8807967   .0305094    -3.66   0.000      .822984    .9426706
                rc_x3 |   1.297611   .1196287     2.83   0.005     1.083106    1.554598
                _rcs1 |   2.177066   .0586595    28.87   0.000     2.065078    2.295126
                _rcs2 |   1.071884   .0075279     9.88   0.000     1.057231    1.086741
                _rcs3 |   1.033961   .0056547     6.11   0.000     1.022937    1.045104
                _rcs4 |   1.019485   .0038677     5.09   0.000     1.011932    1.027094
                _rcs5 |   1.012627   .0028211     4.50   0.000     1.007113    1.018171
                _rcs6 |    1.01034   .0021956     4.73   0.000     1.006046    1.014653
  _rcs_mot_egr_early1 |   .8978523   .0271955    -3.56   0.000     .8461013    .9527685
   _rcs_mot_egr_late1 |   .9205885   .0267904    -2.84   0.004     .8695497     .974623
                _cons |   7.4e+142   1.2e+144    20.43   0.000     1.5e+129    3.7e+156
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. // sacar matrices
. matrix table_r2 = r(table)

. 
. // Column and rownames
. global rownms2: rown r(table)

. di "$rownms2"
b se z pvalue ll ul df crit eform

. global colnms2: coln r(table)

. di "$colnms2"
mot_egr_early mot_egr_late tr_mod2 sex_dum2 edad_ini_cons esc1 esc2 sus_prin2 sus_prin3 sus_prin4 sus_prin5 fr_cons_sus_prin2 fr_cons_sus_prin3 fr_cons_sus_prin4 fr_cons_sus_p
> rin5 cond_ocu2 cond_ocu3 cond_ocu4 cond_ocu5 cond_ocu6 policonsumo num_hij2 tenviv1 tenviv2 tenviv4 tenviv5 mzone2 mzone3 n_off_vio n_off_acq n_off_sud n_off_oth psy_com2 de
> p2 rural2 rural3 porc_pobr susini2 susini3 susini4 susini5 ano_nac_corr cohab2 cohab3 cohab4 fis_com2 rc_x1 rc_x2 rc_x3 _rcs1 _rcs2 _rcs3 _rcs4 _rcs5 _rcs6 _rcs_mot_egr_earl
> y1 _rcs_mot_egr_late1 _cons _d_rcs1 _d_rcs2 _d_rcs3 _d_rcs4 _d_rcs5 _d_rcs6 _d_rcs_mot_egr_early1 _d_rcs_mot_egr_late1

. local reqs2 : roweq r(table) //coleq

. di "`reqs2'"
_ _ _ _ _ _ _ _ _

. global ceqs2 : coleq r(table) //coleq

. di "`ceqs2'"


. local cname2 : colfullnames r(table)

. di "`cname2'"
xb:mot_egr_early xb:mot_egr_late xb:tr_mod2 xb:sex_dum2 xb:edad_ini_cons xb:esc1 xb:esc2 xb:sus_prin2 xb:sus_prin3 xb:sus_prin4 xb:sus_prin5 xb:fr_cons_sus_prin2 xb:fr_cons_su
> s_prin3 xb:fr_cons_sus_prin4 xb:fr_cons_sus_prin5 xb:cond_ocu2 xb:cond_ocu3 xb:cond_ocu4 xb:cond_ocu5 xb:cond_ocu6 xb:policonsumo xb:num_hij2 xb:tenviv1 xb:tenviv2 xb:tenviv
> 4 xb:tenviv5 xb:mzone2 xb:mzone3 xb:n_off_vio xb:n_off_acq xb:n_off_sud xb:n_off_oth xb:psy_com2 xb:dep2 xb:rural2 xb:rural3 xb:porc_pobr xb:susini2 xb:susini3 xb:susini4 xb
> :susini5 xb:ano_nac_corr xb:cohab2 xb:cohab3 xb:cohab4 xb:fis_com2 xb:rc_x1 xb:rc_x2 xb:rc_x3 xb:_rcs1 xb:_rcs2 xb:_rcs3 xb:_rcs4 xb:_rcs5 xb:_rcs6 xb:_rcs_mot_egr_early1 xb
> :_rcs_mot_egr_late1 xb:_cons dxb:_d_rcs1 dxb:_d_rcs2 dxb:_d_rcs3 dxb:_d_rcs4 dxb:_d_rcs5 dxb:_d_rcs6 dxb:_d_rcs_mot_egr_early1 dxb:_d_rcs_mot_egr_late1

. 
. // Eliminate equations
. matrix coleq table_r2 = ""

. 
. // Subset matrix by column names
. *https://www.stata.com/manuals13/u14.pdf
. *https://www.stata.com/manuals13/dfunctions.pdf#dfunctionsDescriptionMatrixfunctionsreturningamatrix
. *
. matrix A2 = table_r2[1... , "mot_egr_early"], table_r2[1... , "mot_egr_late"], table_r2[1... , "_rcs1".." _rcs_mot_egr_late1"], table_r2[1... , "_d_rcs1".." _d_rcs_mot_egr_l
> ate1"]

. matrix mod2= A2["b","mot_egr_early".."_d_rcs_mot_egr_late1"] \ A2["ll","mot_egr_early".."_d_rcs_mot_egr_late1"] \ A2["ul","mot_egr_early".."_d_rcs_mot_egr_early1"...] \ A2["
> pvalue","mot_egr_early".."_d_rcs_mot_egr_early1"...]  // three dots, until the last

. 
. //make another matrix
. mat mod2b= mod2

. 
. //mata: mata drop st_trans_matrix()
. mata:
------------------------------------------------- mata (type end to exit) -----------------------------------------------------------------------------------------------------
: void st_transpose_matrix(string scalar matname)
> {
>     // Convert Stata matrix to Mata matrix
>     M = st_matrix(matname)
> 
>     // Transpose the matrix
>     transposed_M = M'
> 
>     // Convert Mata matrix to Stata matrix
>     st_matrix(matname, transposed_M)
> }

: end
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

. 
. //transpose function
. mata: st_transpose_matrix("mod2b")

. 
. //move colnames and rownames to transpose
. local cnames2 :  rownames mod2

. di " `cnames2'"
 b ll ul pvalue

. mat colnames mod2b = `cnames2'

. local rnames2 :  colnames mod2 

. mat rownames mod2b = `rnames2' 

. 
. //export
. esttab matrix(mod2b) using "mat_tab2.html", replace
(output written to mat_tab2.html)

. 

Condemnatory Sentence, Listwise

. cap qui noi clear all

. qui estread using "mariel_feb_23.sters"

. estimates replay m_nostag_rp6_tvc_1, eform

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Model m_nostag_rp6_tvc_1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Log likelihood = -54443.187                     Number of obs     =     60,253

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |   1.728953   .0499925    18.94   0.000     1.633694    1.829766
         mot_egr_late |   1.577917   .0370653    19.42   0.000     1.506917    1.652262
              tr_mod2 |   1.218636   .0262221     9.19   0.000      1.16831    1.271129
             sex_dum2 |   .7600293    .016327   -12.77   0.000     .7286932    .7927129
        edad_ini_cons |   .9868996   .0019513    -6.67   0.000     .9830825    .9907315
                 esc1 |   1.128982   .0298192     4.59   0.000     1.072025    1.188966
                 esc2 |   1.088746    .025948     3.57   0.000     1.039058     1.14081
            sus_prin2 |   1.066729   .0297425     2.32   0.021     1.009999    1.126646
            sus_prin3 |   1.392948   .0326517    14.14   0.000       1.3304    1.458437
            sus_prin4 |   1.076603   .0378667     2.10   0.036     1.004886    1.153438
            sus_prin5 |   1.141834   .0825502     1.83   0.067     .9909792    1.315654
    fr_cons_sus_prin2 |    .920203   .0450222    -1.70   0.089     .8360601    1.012814
    fr_cons_sus_prin3 |   .9969857   .0395705    -0.08   0.939     .9223689    1.077639
    fr_cons_sus_prin4 |   1.008748   .0420384     0.21   0.834     .9296295      1.0946
    fr_cons_sus_prin5 |   1.030657   .0409393     0.76   0.447     .9534613    1.114103
            cond_ocu2 |   1.017891   .0318157     0.57   0.570     .9574048    1.082198
            cond_ocu3 |   1.005554   .1418086     0.04   0.969     .7627188    1.325704
            cond_ocu4 |   1.104285   .0399243     2.74   0.006     1.028743    1.185375
            cond_ocu5 |   1.161881    .089036     1.96   0.050     .9998462    1.350175
            cond_ocu6 |   1.131352   .0207262     6.74   0.000      1.09145    1.172713
          policonsumo |   1.026642   .0224184     1.20   0.229     .9836297    1.071535
             num_hij2 |   1.165174   .0227514     7.83   0.000     1.121424     1.21063
              tenviv1 |   1.152096    .075424     2.16   0.031     1.013358    1.309827
              tenviv2 |   1.127523   .0494075     2.74   0.006     1.034728     1.22864
              tenviv4 |   1.037621   .0237463     1.61   0.107     .9921074    1.085222
              tenviv5 |   1.003652   .0179934     0.20   0.839     .9689976    1.039545
               mzone2 |   1.302629   .0273768    12.58   0.000     1.250061    1.357407
               mzone3 |   1.464532   .0421233    13.27   0.000     1.384256    1.549464
            n_off_vio |   1.355274   .0258706    15.93   0.000     1.305506     1.40694
            n_off_acq |   1.814333   .0324517    33.31   0.000     1.751831    1.879065
            n_off_sud |   1.256841   .0233136    12.32   0.000     1.211967    1.303375
            n_off_oth |   1.360377   .0257473    16.26   0.000     1.310838    1.411788
             psy_com2 |    1.07078   .0257019     2.85   0.004     1.021572    1.122359
             psy_com3 |    1.05835   .0187998     3.19   0.001     1.022137    1.095846
                 dep2 |   1.019981   .0195475     1.03   0.302     .9823791    1.059022
               rural2 |   1.028789   .0287124     1.02   0.309     .9740256    1.086632
               rural3 |   1.054563   .0324416     1.73   0.084     .9928578    1.120104
            porc_pobr |   1.228279   .1453468     1.74   0.082      .974027    1.548898
              susini2 |   1.095891   .0455133     2.20   0.027      1.01022    1.188826
              susini3 |   1.122648   .0372602     3.49   0.000     1.051944    1.198104
              susini4 |   1.082362   .0193437     4.43   0.000     1.045105    1.120947
              susini5 |   1.129855    .056192     2.45   0.014     1.024918    1.245535
         ano_nac_corr |    .874961    .003746   -31.20   0.000     .8676497    .8823339
               cohab2 |   .9707827   .0310641    -0.93   0.354     .9117682    1.033617
               cohab3 |   .9914812   .0390175    -0.22   0.828      .917883    1.070981
               cohab4 |   .9524348   .0296215    -1.57   0.117     .8961117    1.012298
             fis_com2 |   1.027195   .0166785     1.65   0.098     .9950202     1.06041
             fis_com3 |   .9022046   .0336831    -2.76   0.006     .8385445    .9706976
                rc_x1 |   .8517336   .0048089   -28.42   0.000     .8423604    .8612112
                rc_x2 |   1.028766   .0186435     1.56   0.118      .992867    1.065963
                rc_x3 |   .8953119   .0414545    -2.39   0.017     .8176403    .9803619
                _rcs1 |   2.632098   .0397141    64.14   0.000     2.555399    2.711098
                _rcs2 |   1.104931   .0062859    17.54   0.000     1.092679     1.11732
                _rcs3 |   1.042542   .0040782    10.65   0.000      1.03458    1.050566
                _rcs4 |   1.020136   .0025116     8.10   0.000     1.015225    1.025071
                _rcs5 |   1.011801   .0017195     6.90   0.000     1.008437    1.015177
                _rcs6 |   1.006751    .001313     5.16   0.000     1.004181    1.009328
  _rcs_mot_egr_early1 |     .90547    .016121    -5.58   0.000     .8744183    .9376243
   _rcs_mot_egr_late1 |   .9427967   .0154771    -3.59   0.000     .9129449    .9736246
                _cons |   2.9e+115   2.5e+116    30.83   0.000     1.3e+108    6.4e+122
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. // sacar matrices
. matrix table_r3 = r(table)

. 
. // Column and rownames
. global rownms3: rown r(table)

. di "$rownms3"
b se z pvalue ll ul df crit eform

. global colnms3: coln r(table)

. di "$colnms3"
mot_egr_early mot_egr_late tr_mod2 sex_dum2 edad_ini_cons esc1 esc2 sus_prin2 sus_prin3 sus_prin4 sus_prin5 fr_cons_sus_prin2 fr_cons_sus_prin3 fr_cons_sus_prin4 fr_cons_sus_p
> rin5 cond_ocu2 cond_ocu3 cond_ocu4 cond_ocu5 cond_ocu6 policonsumo num_hij2 tenviv1 tenviv2 tenviv4 tenviv5 mzone2 mzone3 n_off_vio n_off_acq n_off_sud n_off_oth psy_com2 ps
> y_com3 dep2 rural2 rural3 porc_pobr susini2 susini3 susini4 susini5 ano_nac_corr cohab2 cohab3 cohab4 fis_com2 fis_com3 rc_x1 rc_x2 rc_x3 _rcs1 _rcs2 _rcs3 _rcs4 _rcs5 _rcs6
>  _rcs_mot_egr_early1 _rcs_mot_egr_late1 _cons _d_rcs1 _d_rcs2 _d_rcs3 _d_rcs4 _d_rcs5 _d_rcs6 _d_rcs_mot_egr_early1 _d_rcs_mot_egr_late1

. local reqs3 : roweq r(table) //coleq

. di "`reqs3'"
_ _ _ _ _ _ _ _ _

. global ceqs3 : coleq r(table) //coleq

. di "`ceqs3'"


. local cname3 : colfullnames r(table)

. di "`cname3'"
xb:mot_egr_early xb:mot_egr_late xb:tr_mod2 xb:sex_dum2 xb:edad_ini_cons xb:esc1 xb:esc2 xb:sus_prin2 xb:sus_prin3 xb:sus_prin4 xb:sus_prin5 xb:fr_cons_sus_prin2 xb:fr_cons_su
> s_prin3 xb:fr_cons_sus_prin4 xb:fr_cons_sus_prin5 xb:cond_ocu2 xb:cond_ocu3 xb:cond_ocu4 xb:cond_ocu5 xb:cond_ocu6 xb:policonsumo xb:num_hij2 xb:tenviv1 xb:tenviv2 xb:tenviv
> 4 xb:tenviv5 xb:mzone2 xb:mzone3 xb:n_off_vio xb:n_off_acq xb:n_off_sud xb:n_off_oth xb:psy_com2 xb:psy_com3 xb:dep2 xb:rural2 xb:rural3 xb:porc_pobr xb:susini2 xb:susini3 x
> b:susini4 xb:susini5 xb:ano_nac_corr xb:cohab2 xb:cohab3 xb:cohab4 xb:fis_com2 xb:fis_com3 xb:rc_x1 xb:rc_x2 xb:rc_x3 xb:_rcs1 xb:_rcs2 xb:_rcs3 xb:_rcs4 xb:_rcs5 xb:_rcs6 x
> b:_rcs_mot_egr_early1 xb:_rcs_mot_egr_late1 xb:_cons dxb:_d_rcs1 dxb:_d_rcs2 dxb:_d_rcs3 dxb:_d_rcs4 dxb:_d_rcs5 dxb:_d_rcs6 dxb:_d_rcs_mot_egr_early1 dxb:_d_rcs_mot_egr_lat
> e1

. 
. // Eliminate equations
. matrix coleq table_r3 = ""

. 
. local cname3 : colfullnames table_r3

. di "`cname3'"
mot_egr_early mot_egr_late tr_mod2 sex_dum2 edad_ini_cons esc1 esc2 sus_prin2 sus_prin3 sus_prin4 sus_prin5 fr_cons_sus_prin2 fr_cons_sus_prin3 fr_cons_sus_prin4 fr_cons_sus_p
> rin5 cond_ocu2 cond_ocu3 cond_ocu4 cond_ocu5 cond_ocu6 policonsumo num_hij2 tenviv1 tenviv2 tenviv4 tenviv5 mzone2 mzone3 n_off_vio n_off_acq n_off_sud n_off_oth psy_com2 ps
> y_com3 dep2 rural2 rural3 porc_pobr susini2 susini3 susini4 susini5 ano_nac_corr cohab2 cohab3 cohab4 fis_com2 fis_com3 rc_x1 rc_x2 rc_x3 _rcs1 _rcs2 _rcs3 _rcs4 _rcs5 _rcs6
>  _rcs_mot_egr_early1 _rcs_mot_egr_late1 _cons _d_rcs1 _d_rcs2 _d_rcs3 _d_rcs4 _d_rcs5 _d_rcs6 _d_rcs_mot_egr_early1 _d_rcs_mot_egr_late1

. 
. // Subset matrix by column names
. *https://www.stata.com/manuals13/u14.pdf
. *https://www.stata.com/manuals13/dfunctions.pdf#dfunctionsDescriptionMatrixfunctionsreturningamatrix
. *
. matrix A3 = table_r3[1... , "mot_egr_early"], table_r3[1... , "mot_egr_late"], table_r3[1... , "_rcs1".." _rcs_mot_egr_late1"], table_r3[1... , "_d_rcs1".." _d_rcs_mot_egr_l
> ate1"]

. matrix mod3= A3["b","mot_egr_early".."_d_rcs_mot_egr_late1"] \ A3["ll","mot_egr_early".."_d_rcs_mot_egr_late1"] \ A3["ul","mot_egr_early".."_d_rcs_mot_egr_early1"...] \ A3["
> pvalue","mot_egr_early".."_d_rcs_mot_egr_early1"...]  // three dots, until the last

. 
. //make another matrix
. mat mod3b= mod3

. 
. //mata: mata drop st_transpose_matrix()
. mata:
------------------------------------------------- mata (type end to exit) -----------------------------------------------------------------------------------------------------
: void st_transpose_matrix(string scalar matname)
> {
>     // Convert Stata matrix to Mata matrix
>     M = st_matrix(matname)
> 
>     // Transpose the matrix
>     transposed_M = M'
> 
>     // Convert Mata matrix to Stata matrix
>     st_matrix(matname, transposed_M)
> }

: end
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

. 
. //transpose function
. mata: st_transpose_matrix("mod3b")

. 
. //move colnames and rownames to transpose
. local cnames3 :  rownames mod3

. di " `cnames3'"
 b ll ul pvalue

. mat colnames mod3b = `cnames3'

. local rnames3 :  colfullnames mod3

. mat rownames mod3b = `rnames3' 

. di " `names3'"
 

. //export
. esttab matrix(mod3b) using "mat_tab3.html", replace
(output written to mat_tab3.html)

Imprisonment, Listwise

. cap qui noi clear all

. qui estread using "mariel_feb_23_2.sters"

. estimates replay m_nostag_rp6_tvc_1, eform

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Model m_nostag_rp6_tvc_1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Log likelihood = -16977.437                     Number of obs     =     60,253

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |   2.012536     .12695    11.09   0.000     1.778485    2.277389
         mot_egr_late |   1.694464   .0920751     9.71   0.000     1.523278    1.884888
              tr_mod2 |   1.218438   .0518245     4.65   0.000     1.120982    1.324366
             sex_dum2 |    .607298   .0295195   -10.26   0.000     .5521115    .6680008
        edad_ini_cons |   .9714319   .0047127    -5.97   0.000     .9622389    .9807126
                 esc1 |   1.430409   .0886472     5.78   0.000     1.266802    1.615147
                 esc2 |   1.264154    .073243     4.05   0.000     1.128451    1.416176
            sus_prin2 |   1.157338   .0782559     2.16   0.031     1.013688    1.321344
            sus_prin3 |   1.681938   .0916982     9.54   0.000     1.511482    1.871617
            sus_prin4 |    1.17118   .0933799     1.98   0.048     1.001743    1.369277
            sus_prin5 |   1.590815   .2391632     3.09   0.002     1.184813    2.135941
    fr_cons_sus_prin2 |    .967409   .1088579    -0.29   0.768     .7759406    1.206124
    fr_cons_sus_prin3 |   .9785847   .0894334    -0.24   0.813     .8181005    1.170551
    fr_cons_sus_prin4 |   1.003281   .0951204     0.03   0.972     .8331449    1.208159
    fr_cons_sus_prin5 |   1.030036   .0934609     0.33   0.744     .8622201    1.230514
            cond_ocu2 |   1.048814   .0745353     0.67   0.502     .9124447    1.205563
            cond_ocu3 |   1.146648   .3093534     0.51   0.612     .6757487    1.945697
            cond_ocu4 |   1.220389   .0890058     2.73   0.006     1.057835    1.407921
            cond_ocu5 |   1.057984   .1641719     0.36   0.716     .7805393    1.434048
            cond_ocu6 |   1.189485   .0465057     4.44   0.000     1.101741    1.284218
          policonsumo |   .9915966   .0486117    -0.17   0.863     .9007536    1.091601
             num_hij2 |   1.125554   .0447828     2.97   0.003     1.041117     1.21684
              tenviv1 |   1.067279   .1350448     0.51   0.607     .8328636    1.367672
              tenviv2 |   1.125202   .0969405     1.37   0.171     .9503774    1.332185
              tenviv4 |   1.038047   .0510085     0.76   0.447     .9427354    1.142994
              tenviv5 |   1.010717   .0383263     0.28   0.779     .9383225    1.088697
               mzone2 |   1.450399   .0608534     8.86   0.000     1.335901    1.574711
               mzone3 |   1.528535   .0965347     6.72   0.000     1.350572    1.729948
            n_off_vio |   1.466613   .0554377    10.13   0.000     1.361884    1.579395
            n_off_acq |   2.798335   .0972513    29.61   0.000     2.614073    2.995586
            n_off_sud |   1.390646   .0507004     9.05   0.000     1.294743    1.493654
            n_off_oth |   1.736015   .0634121    15.10   0.000     1.616074    1.864858
             psy_com2 |   1.118023   .0550376     2.27   0.023     1.015191     1.23127
             psy_com3 |   1.100216   .0424081     2.48   0.013      1.02016    1.186555
                 dep2 |   1.036419   .0441269     0.84   0.401     .9534424    1.126617
               rural2 |    .898513   .0559683    -1.72   0.086      .795249    1.015186
               rural3 |   .8606054   .0595695    -2.17   0.030     .7514247    .9856499
            porc_pobr |   1.571197   .3932657     1.81   0.071      .962005     2.56616
              susini2 |   1.188536   .1083406     1.89   0.058     .9940805    1.421031
              susini3 |   1.270308   .0818754     3.71   0.000     1.119558    1.441358
              susini4 |    1.18061   .0440211     4.45   0.000     1.097408    1.270121
              susini5 |   1.421915   .1320064     3.79   0.000     1.185361    1.705677
         ano_nac_corr |   .8500967   .0080232   -17.21   0.000     .8345161    .8659682
               cohab2 |   .8802602   .0591132    -1.90   0.058     .7717015     1.00409
               cohab3 |   1.075106   .0859654     0.91   0.365     .9191564    1.257516
               cohab4 |    .964041   .0641775    -0.55   0.582      .846116    1.098401
             fis_com2 |   1.057973   .0364668     1.63   0.102     .9888599    1.131916
             fis_com3 |   .8191694   .0709746    -2.30   0.021     .6912319    .9707863
                rc_x1 |   .8503726   .0101848   -13.53   0.000     .8306432    .8705706
                rc_x2 |   .8817405   .0351634    -3.16   0.002      .815446    .9534245
                rc_x3 |   1.277763   .1359053     2.30   0.021     1.037326    1.573931
                _rcs1 |   2.200956   .0694371    25.01   0.000     2.068984    2.341346
                _rcs2 |   1.065717   .0083576     8.12   0.000     1.049462    1.082225
                _rcs3 |   1.033663    .006363     5.38   0.000     1.021266     1.04621
                _rcs4 |   1.017806   .0044294     4.06   0.000     1.009161    1.026524
                _rcs5 |   1.010267   .0032115     3.21   0.001     1.003993    1.016581
                _rcs6 |   1.008379   .0025225     3.34   0.001     1.003447    1.013335
  _rcs_mot_egr_early1 |   .8926688   .0314254    -3.23   0.001     .8331531    .9564359
   _rcs_mot_egr_late1 |   .9136598   .0309637    -2.66   0.008     .8549437    .9764086
                _cons |   1.4e+139   2.7e+140    16.86   0.000     9.7e+122    2.2e+155
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. // sacar matrices
. matrix table_r4 = r(table)

. 
. // Column and rownames
. global rownms4: rown r(table)

. di "$rownms4"
b se z pvalue ll ul df crit eform

. global colnms4: coln r(table)

. di "$colnms4"
mot_egr_early mot_egr_late tr_mod2 sex_dum2 edad_ini_cons esc1 esc2 sus_prin2 sus_prin3 sus_prin4 sus_prin5 fr_cons_sus_prin2 fr_cons_sus_prin3 fr_cons_sus_prin4 fr_cons_sus_p
> rin5 cond_ocu2 cond_ocu3 cond_ocu4 cond_ocu5 cond_ocu6 policonsumo num_hij2 tenviv1 tenviv2 tenviv4 tenviv5 mzone2 mzone3 n_off_vio n_off_acq n_off_sud n_off_oth psy_com2 ps
> y_com3 dep2 rural2 rural3 porc_pobr susini2 susini3 susini4 susini5 ano_nac_corr cohab2 cohab3 cohab4 fis_com2 fis_com3 rc_x1 rc_x2 rc_x3 _rcs1 _rcs2 _rcs3 _rcs4 _rcs5 _rcs6
>  _rcs_mot_egr_early1 _rcs_mot_egr_late1 _cons _d_rcs1 _d_rcs2 _d_rcs3 _d_rcs4 _d_rcs5 _d_rcs6 _d_rcs_mot_egr_early1 _d_rcs_mot_egr_late1

. local reqs4 : roweq r(table) //coleq

. di "`reqs4'"
_ _ _ _ _ _ _ _ _

. global ceqs4 : coleq r(table) //coleq

. di "`ceqs4'"


. local cname4 : colfullnames r(table)

. di "`cname4'"
xb:mot_egr_early xb:mot_egr_late xb:tr_mod2 xb:sex_dum2 xb:edad_ini_cons xb:esc1 xb:esc2 xb:sus_prin2 xb:sus_prin3 xb:sus_prin4 xb:sus_prin5 xb:fr_cons_sus_prin2 xb:fr_cons_su
> s_prin3 xb:fr_cons_sus_prin4 xb:fr_cons_sus_prin5 xb:cond_ocu2 xb:cond_ocu3 xb:cond_ocu4 xb:cond_ocu5 xb:cond_ocu6 xb:policonsumo xb:num_hij2 xb:tenviv1 xb:tenviv2 xb:tenviv
> 4 xb:tenviv5 xb:mzone2 xb:mzone3 xb:n_off_vio xb:n_off_acq xb:n_off_sud xb:n_off_oth xb:psy_com2 xb:psy_com3 xb:dep2 xb:rural2 xb:rural3 xb:porc_pobr xb:susini2 xb:susini3 x
> b:susini4 xb:susini5 xb:ano_nac_corr xb:cohab2 xb:cohab3 xb:cohab4 xb:fis_com2 xb:fis_com3 xb:rc_x1 xb:rc_x2 xb:rc_x3 xb:_rcs1 xb:_rcs2 xb:_rcs3 xb:_rcs4 xb:_rcs5 xb:_rcs6 x
> b:_rcs_mot_egr_early1 xb:_rcs_mot_egr_late1 xb:_cons dxb:_d_rcs1 dxb:_d_rcs2 dxb:_d_rcs3 dxb:_d_rcs4 dxb:_d_rcs5 dxb:_d_rcs6 dxb:_d_rcs_mot_egr_early1 dxb:_d_rcs_mot_egr_lat
> e1

. 
. // Eliminate equations
. matrix coleq table_r4 = ""

. 
. // Subset matrix by column names
. *https://www.stata.com/manuals14/u14.pdf
. *https://www.stata.com/manuals14/dfunctions.pdf#dfunctionsDescriptionMatrixfunctionsreturningamatrix
. *
. matrix A4 = table_r4[1... , "mot_egr_early"], table_r4[1... , "mot_egr_late"], table_r4[1... , "_rcs1".." _rcs_mot_egr_late1"], table_r4[1... , "_d_rcs1".." _d_rcs_mot_egr_l
> ate1"]

. matrix mod4= A4["b","mot_egr_early".."_d_rcs_mot_egr_late1"] \ A4["ll","mot_egr_early".."_d_rcs_mot_egr_late1"] \ A4["ul","mot_egr_early".."_d_rcs_mot_egr_early1"...] \ A4["
> pvalue","mot_egr_early".."_d_rcs_mot_egr_early1"...]  // three dots, until the last

. 
. //make another matrix
. mat mod4b= mod4

. 
. //mata: mata drop st_trans_matrix()
. mata:
------------------------------------------------- mata (type end to exit) -----------------------------------------------------------------------------------------------------
: void st_transpose_matrix(string scalar matname)
> {
>     // Convert Stata matrix to Mata matrix
>     M = st_matrix(matname)
> 
>     // Transpose the matrix
>     transposed_M = M'
> 
>     // Convert Mata matrix to Stata matrix
>     st_matrix(matname, transposed_M)
> }

: end
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

. 
. //transpose function
. mata: st_transpose_matrix("mod4b")

. 
. //move colnames and rownames to transpose
. local cnames4 :  rownames mod4

. di " `cnames4'"
 b ll ul pvalue

. mat colnames mod4b = `cnames4'

. local rnames4 :  colnames mod4 

. mat rownames mod4b = `rnames4' 

. 
. //export
. esttab matrix(mod4b) using "mat_tab4.html", replace
(output written to mat_tab4.html)

*#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#: *#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#: *#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:

Transform figures to Restricted Mean Time Lost

. use mariel_feb_23_m1.dta, clear 

. estread using "mariel_feb_23_2_m1.sters"

-------------------------------------------------------------------------
        name | command      depvar       npar  title 
-------------+-----------------------------------------------------------
 full_spline | stcox        _t             72  
 linear_term | stcox        _t             70  
m_nostag_r~1 | stpm2        mult. depvar   56  
m_nostag_r~2 | stpm2        mult. depvar   60  
m_nostag_r~3 | stpm2        mult. depvar   64  
m_nostag_r~4 | stpm2        mult. depvar   68  
m_nostag_r~5 | stpm2        mult. depvar   72  
m_nostag_r~6 | stpm2        mult. depvar   76  
m_nostag_r~7 | stpm2        mult. depvar   80  
m_nostag_r~1 | stpm2        mult. depvar   58  
m_nostag_r~2 | stpm2        mult. depvar   62  
m_nostag_r~3 | stpm2        mult. depvar   66  
m_nostag_r~4 | stpm2        mult. depvar   70  
m_nostag_r~5 | stpm2        mult. depvar   74  
m_nostag_r~6 | stpm2        mult. depvar   78  
m_nostag_r~7 | stpm2        mult. depvar   82  
m_nostag_r~1 | stpm2        mult. depvar   60  
m_nostag_r~2 | stpm2        mult. depvar   64  
m_nostag_r~3 | stpm2        mult. depvar   68  
m_nostag_r~4 | stpm2        mult. depvar   72  
m_nostag_r~5 | stpm2        mult. depvar   76  
m_nostag_r~6 | stpm2        mult. depvar   80  
m_nostag_r~7 | stpm2        mult. depvar   84  
m_nostag_r~1 | stpm2        mult. depvar   62  
m_nostag_r~2 | stpm2        mult. depvar   66  
m_nostag_r~3 | stpm2        mult. depvar   70  
m_nostag_r~4 | stpm2        mult. depvar   74  
m_nostag_r~5 | stpm2        mult. depvar   78  
m_nostag_r~6 | stpm2        mult. depvar   82  
m_nostag_r~7 | stpm2        mult. depvar   86  
m_nostag_r~1 | stpm2        mult. depvar   64  
m_nostag_r~2 | stpm2        mult. depvar   68  
m_nostag_r~3 | stpm2        mult. depvar   72  
m_nostag_r~4 | stpm2        mult. depvar   76  
m_nostag_r~5 | stpm2        mult. depvar   80  
m_nostag_r~6 | stpm2        mult. depvar   84  
m_nostag_r~7 | stpm2        mult. depvar   88  
m_nostag_r~1 | stpm2        mult. depvar   66  
m_nostag_r~2 | stpm2        mult. depvar   70  
m_nostag_r~3 | stpm2        mult. depvar   74  
m_nostag_r~4 | stpm2        mult. depvar   78  
m_nostag_r~5 | stpm2        mult. depvar   82  
m_nostag_r~6 | stpm2        mult. depvar   86  
m_nostag_r~7 | stpm2        mult. depvar   90  
m_nostag_r~1 | stpm2        mult. depvar   68  
m_nostag_r~2 | stpm2        mult. depvar   72  
m_nostag_r~3 | stpm2        mult. depvar   76  
m_nostag_r~4 | stpm2        mult. depvar   80  
m_nostag_r~5 | stpm2        mult. depvar   84  
m_nostag_r~6 | stpm2        mult. depvar   88  
m_nostag_r~7 | stpm2        mult. depvar   92  
m_nostag_r~1 | stpm2        mult. depvar   70  
m_nostag_r~2 | stpm2        mult. depvar   74  
m_nostag_r~3 | stpm2        mult. depvar   78  
m_nostag_r~4 | stpm2        mult. depvar   82  
m_nostag_r~5 | stpm2        mult. depvar   86  
m_nostag_r~6 | stpm2        mult. depvar   90  
m_nostag_r~7 | stpm2        mult. depvar   94  
m_nostag_r~1 | stpm2        mult. depvar   72  
m_nostag_r~2 | stpm2        mult. depvar   76  
m_nostag_r~3 | stpm2        mult. depvar   80  
m_nostag_r~4 | stpm2        mult. depvar   84  
m_nostag_r~5 | stpm2        mult. depvar   88  
m_nostag_r~6 | stpm2        mult. depvar   92  
m_nostag_r~7 | stpm2        mult. depvar   96  
m_nostag_r~1 | stpm2        mult. depvar   74  
m_nostag_r~2 | stpm2        mult. depvar   78  
m_nostag_r~3 | stpm2        mult. depvar   82  
m_nostag_r~4 | stpm2        mult. depvar   86  
m_nostag_r~5 | stpm2        mult. depvar   90  
m_nostag_r~6 | stpm2        mult. depvar   94  
m_nostag_r~7 | stpm2        mult. depvar   98  
m_stipw_no~1 | stpm2        mult. depvar    6  
m_stipw_no~2 | stpm2        mult. depvar    8  
m_stipw_no~3 | stpm2        mult. depvar   10  
m_stipw_no~4 | stpm2        mult. depvar   12  
m_stipw_no~5 | stpm2        mult. depvar   14  
m_stipw_no~6 | stpm2        mult. depvar   16  
m_stipw_no~7 | stpm2        mult. depvar   18  
m_stipw_no~1 | stpm2        mult. depvar    8  
m_stipw_no~2 | stpm2        mult. depvar   10  
m_stipw_no~3 | stpm2        mult. depvar   12  
m_stipw_no~4 | stpm2        mult. depvar   14  
m_stipw_no~5 | stpm2        mult. depvar   16  
m_stipw_no~6 | stpm2        mult. depvar   18  
m_stipw_no~7 | stpm2        mult. depvar   20  
m_stipw_no~1 | stpm2        mult. depvar   10  
m_stipw_no~2 | stpm2        mult. depvar   12  
m_stipw_no~3 | stpm2        mult. depvar   14  
m_stipw_no~4 | stpm2        mult. depvar   16  
m_stipw_no~5 | stpm2        mult. depvar   18  
m_stipw_no~6 | stpm2        mult. depvar   20  
m_stipw_no~7 | stpm2        mult. depvar   22  
m_stipw_no~1 | stpm2        mult. depvar   12  
m_stipw_no~2 | stpm2        mult. depvar   14  
m_stipw_no~3 | stpm2        mult. depvar   16  
m_stipw_no~4 | stpm2        mult. depvar   18  
m_stipw_no~5 | stpm2        mult. depvar   20  
m_stipw_no~6 | stpm2        mult. depvar   22  
m_stipw_no~7 | stpm2        mult. depvar   24  
m_stipw_no~1 | stpm2        mult. depvar   14  
m_stipw_no~2 | stpm2        mult. depvar   16  
m_stipw_no~3 | stpm2        mult. depvar   18  
m_stipw_no~4 | stpm2        mult. depvar   20  
m_stipw_no~5 | stpm2        mult. depvar   22  
m_stipw_no~6 | stpm2        mult. depvar   24  
m_stipw_no~7 | stpm2        mult. depvar   26  
m_stipw_no~1 | stpm2        mult. depvar   16  
m_stipw_no~2 | stpm2        mult. depvar   18  
m_stipw_no~3 | stpm2        mult. depvar   20  
m_stipw_no~4 | stpm2        mult. depvar   22  
m_stipw_no~5 | stpm2        mult. depvar   24  
m_stipw_no~6 | stpm2        mult. depvar   26  
m_stipw_no~7 | stpm2        mult. depvar   28  
m_stipw_no~1 | stpm2        mult. depvar   18  
m_stipw_no~2 | stpm2        mult. depvar   20  
m_stipw_no~3 | stpm2        mult. depvar   22  
m_stipw_no~4 | stpm2        mult. depvar   24  
m_stipw_no~5 | stpm2        mult. depvar   26  
m_stipw_no~6 | stpm2        mult. depvar   28  
m_stipw_no~7 | stpm2        mult. depvar   30  
m_stipw_no~1 | stpm2        mult. depvar   20  
m_stipw_no~2 | stpm2        mult. depvar   22  
m_stipw_no~3 | stpm2        mult. depvar   24  
m_stipw_no~4 | stpm2        mult. depvar   26  
m_stipw_no~5 | stpm2        mult. depvar   28  
m_stipw_no~6 | stpm2        mult. depvar   30  
m_stipw_no~7 | stpm2        mult. depvar   32  
m_stipw_no~1 | stpm2        mult. depvar   22  
m_stipw_no~2 | stpm2        mult. depvar   24  
m_stipw_no~3 | stpm2        mult. depvar   26  
m_stipw_no~4 | stpm2        mult. depvar   28  
m_stipw_no~5 | stpm2        mult. depvar   30  
m_stipw_no~6 | stpm2        mult. depvar   32  
m_stipw_no~7 | stpm2        mult. depvar   34  
m_stipw_no~1 | stpm2        mult. depvar   24  
m_stipw_no~2 | stpm2        mult. depvar   26  
m_stipw_no~3 | stpm2        mult. depvar   28  
m_stipw_no~4 | stpm2        mult. depvar   30  
m_stipw_no~5 | stpm2        mult. depvar   32  
m_stipw_no~6 | stpm2        mult. depvar   34  
m_stipw_no~7 | stpm2        mult. depvar   36  
m_stipw_no~p | streg        _t              2  Exponential PH regression
m_stipw_no~i | streg        _t              3  Weibull PH regression
m_stipw_no~m | streg        _t              3  Gompertz PH regression
m_stipw_no~n | streg        _t              3  Lognormal AFT regression
m_stipw_no~g | streg        _t              3  Loglogistic AFT regression
m2_stipw_n~1 | stpm2        mult. depvar    6  
m2_stipw_n~2 | stpm2        mult. depvar    8  
m2_stipw_n~3 | stpm2        mult. depvar   10  
m2_stipw_n~4 | stpm2        mult. depvar   12  
m2_stipw_n~5 | stpm2        mult. depvar   14  
m2_stipw_n~6 | stpm2        mult. depvar   16  
m2_stipw_n~7 | stpm2        mult. depvar   18  
m2_stipw_n~1 | stpm2        mult. depvar    8  
m2_stipw_n~2 | stpm2        mult. depvar   10  
m2_stipw_n~3 | stpm2        mult. depvar   12  
m2_stipw_n~4 | stpm2        mult. depvar   14  
m2_stipw_n~5 | stpm2        mult. depvar   16  
m2_stipw_n~6 | stpm2        mult. depvar   18  
m2_stipw_n~7 | stpm2        mult. depvar   20  
m2_stipw_n~1 | stpm2        mult. depvar   10  
m2_stipw_n~2 | stpm2        mult. depvar   12  
m2_stipw_n~3 | stpm2        mult. depvar   14  
m2_stipw_n~4 | stpm2        mult. depvar   16  
m2_stipw_n~5 | stpm2        mult. depvar   18  
m2_stipw_n~6 | stpm2        mult. depvar   20  
m2_stipw_n~7 | stpm2        mult. depvar   22  
m2_stipw_n~1 | stpm2        mult. depvar   12  
m2_stipw_n~2 | stpm2        mult. depvar   14  
m2_stipw_n~3 | stpm2        mult. depvar   16  
m2_stipw_n~4 | stpm2        mult. depvar   18  
m2_stipw_n~5 | stpm2        mult. depvar   20  
m2_stipw_n~6 | stpm2        mult. depvar   22  
m2_stipw_n~7 | stpm2        mult. depvar   24  
m2_stipw_n~1 | stpm2        mult. depvar   14  
m2_stipw_n~2 | stpm2        mult. depvar   16  
m2_stipw_n~3 | stpm2        mult. depvar   18  
m2_stipw_n~4 | stpm2        mult. depvar   20  
m2_stipw_n~5 | stpm2        mult. depvar   22  
m2_stipw_n~6 | stpm2        mult. depvar   24  
m2_stipw_n~7 | stpm2        mult. depvar   26  
m2_stipw_n~1 | stpm2        mult. depvar   16  
m2_stipw_n~2 | stpm2        mult. depvar   18  
m2_stipw_n~3 | stpm2        mult. depvar   20  
m2_stipw_n~4 | stpm2        mult. depvar   22  
m2_stipw_n~5 | stpm2        mult. depvar   24  
m2_stipw_n~6 | stpm2        mult. depvar   26  
m2_stipw_n~7 | stpm2        mult. depvar   28  
m2_stipw_n~1 | stpm2        mult. depvar   18  
m2_stipw_n~2 | stpm2        mult. depvar   20  
m2_stipw_n~3 | stpm2        mult. depvar   22  
m2_stipw_n~4 | stpm2        mult. depvar   24  
m2_stipw_n~5 | stpm2        mult. depvar   26  
m2_stipw_n~6 | stpm2        mult. depvar   28  
m2_stipw_n~7 | stpm2        mult. depvar   30  
m2_stipw_n~1 | stpm2        mult. depvar   20  
m2_stipw_n~2 | stpm2        mult. depvar   22  
m2_stipw_n~3 | stpm2        mult. depvar   24  
m2_stipw_n~4 | stpm2        mult. depvar   26  
m2_stipw_n~5 | stpm2        mult. depvar   28  
m2_stipw_n~6 | stpm2        mult. depvar   30  
m2_stipw_n~7 | stpm2        mult. depvar   32  
m2_stipw_n~1 | stpm2        mult. depvar   22  
m2_stipw_n~2 | stpm2        mult. depvar   24  
m2_stipw_n~3 | stpm2        mult. depvar   26  
m2_stipw_n~4 | stpm2        mult. depvar   28  
m2_stipw_n~5 | stpm2        mult. depvar   30  
m2_stipw_n~6 | stpm2        mult. depvar   32  
m2_stipw_n~7 | stpm2        mult. depvar   34  
m2_stipw_n~1 | stpm2        mult. depvar   24  
m2_stipw_n~2 | stpm2        mult. depvar   26  
m2_stipw_n~3 | stpm2        mult. depvar   28  
m2_stipw_n~4 | stpm2        mult. depvar   30  
m2_stipw_n~5 | stpm2        mult. depvar   32  
m2_stipw_n~6 | stpm2        mult. depvar   34  
m2_stipw_n~7 | stpm2        mult. depvar   36  
m2_stipw_n~p | streg        _t              2  Exponential PH regression
m2_stipw_n~i | streg        _t              3  Weibull PH regression
m2_stipw_n~m | streg        _t              3  Gompertz PH regression
m2_stipw_n~n | streg        _t              3  Lognormal AFT regression
m2_stipw_n~g | streg        _t              3  Loglogistic AFT regression
m3_stipw_n~1 | stpm2        mult. depvar    6  
m3_stipw_n~2 | stpm2        mult. depvar    8  
m3_stipw_n~3 | stpm2        mult. depvar   10  
m3_stipw_n~4 | stpm2        mult. depvar   12  
m3_stipw_n~5 | stpm2        mult. depvar   14  
m3_stipw_n~6 | stpm2        mult. depvar   16  
m3_stipw_n~7 | stpm2        mult. depvar   18  
m3_stipw_n~1 | stpm2        mult. depvar    8  
m3_stipw_n~2 | stpm2        mult. depvar   10  
m3_stipw_n~3 | stpm2        mult. depvar   12  
m3_stipw_n~4 | stpm2        mult. depvar   14  
m3_stipw_n~5 | stpm2        mult. depvar   16  
m3_stipw_n~6 | stpm2        mult. depvar   18  
m3_stipw_n~7 | stpm2        mult. depvar   20  
m3_stipw_n~1 | stpm2        mult. depvar   10  
m3_stipw_n~2 | stpm2        mult. depvar   12  
m3_stipw_n~3 | stpm2        mult. depvar   14  
m3_stipw_n~4 | stpm2        mult. depvar   16  
m3_stipw_n~5 | stpm2        mult. depvar   18  
m3_stipw_n~6 | stpm2        mult. depvar   20  
m3_stipw_n~7 | stpm2        mult. depvar   22  
m3_stipw_n~1 | stpm2        mult. depvar   12  
m3_stipw_n~2 | stpm2        mult. depvar   14  
m3_stipw_n~3 | stpm2        mult. depvar   16  
m3_stipw_n~4 | stpm2        mult. depvar   18  
m3_stipw_n~5 | stpm2        mult. depvar   20  
m3_stipw_n~6 | stpm2        mult. depvar   22  
m3_stipw_n~7 | stpm2        mult. depvar   24  
m3_stipw_n~1 | stpm2        mult. depvar   14  
m3_stipw_n~2 | stpm2        mult. depvar   16  
m3_stipw_n~3 | stpm2        mult. depvar   18  
m3_stipw_n~4 | stpm2        mult. depvar   20  
m3_stipw_n~5 | stpm2        mult. depvar   22  
m3_stipw_n~6 | stpm2        mult. depvar   24  
m3_stipw_n~7 | stpm2        mult. depvar   26  
m3_stipw_n~1 | stpm2        mult. depvar   16  
m3_stipw_n~2 | stpm2        mult. depvar   18  
m3_stipw_n~3 | stpm2        mult. depvar   20  
m3_stipw_n~4 | stpm2        mult. depvar   22  
m3_stipw_n~5 | stpm2        mult. depvar   24  
m3_stipw_n~6 | stpm2        mult. depvar   26  
m3_stipw_n~7 | stpm2        mult. depvar   28  
m3_stipw_n~1 | stpm2        mult. depvar   18  
m3_stipw_n~2 | stpm2        mult. depvar   20  
m3_stipw_n~3 | stpm2        mult. depvar   22  
m3_stipw_n~4 | stpm2        mult. depvar   24  
m3_stipw_n~5 | stpm2        mult. depvar   26  
m3_stipw_n~6 | stpm2        mult. depvar   28  
m3_stipw_n~7 | stpm2        mult. depvar   30  
m3_stipw_n~1 | stpm2        mult. depvar   20  
m3_stipw_n~2 | stpm2        mult. depvar   22  
m3_stipw_n~3 | stpm2        mult. depvar   24  
m3_stipw_n~4 | stpm2        mult. depvar   26  
m3_stipw_n~5 | stpm2        mult. depvar   28  
m3_stipw_n~6 | stpm2        mult. depvar   30  
m3_stipw_n~7 | stpm2        mult. depvar   32  
m3_stipw_n~1 | stpm2        mult. depvar   22  
m3_stipw_n~2 | stpm2        mult. depvar   24  
m3_stipw_n~3 | stpm2        mult. depvar   26  
m3_stipw_n~4 | stpm2        mult. depvar   28  
m3_stipw_n~5 | stpm2        mult. depvar   30  
m3_stipw_n~6 | stpm2        mult. depvar   32  
m3_stipw_n~7 | stpm2        mult. depvar   34  
m3_stipw_n~1 | stpm2        mult. depvar   24  
m3_stipw_n~2 | stpm2        mult. depvar   26  
m3_stipw_n~3 | stpm2        mult. depvar   28  
m3_stipw_n~4 | stpm2        mult. depvar   30  
m3_stipw_n~5 | stpm2        mult. depvar   32  
m3_stipw_n~6 | stpm2        mult. depvar   34  
m3_stipw_n~7 | stpm2        mult. depvar   36  
m3_stipw_n~p | streg        _t              2  Exponential PH regression
m3_stipw_n~i | streg        _t              3  Weibull PH regression
m3_stipw_n~m | streg        _t              3  Gompertz PH regression
m3_stipw_n~n | streg        _t              3  Lognormal AFT regression
m3_stipw_n~g | streg        _t              3  Loglogistic AFT regression
-------------------------------------------------------------------------

. cap noi drop rmst_h00 rmst_h11 rmst_h22
rmst_h00 ambiguous abbreviation

. 
. gen rmtldiff_tr_comp_early_drop_lci= -rmstdiff_tr_comp_early_drop_lci
(70,808 missing values generated)

. gen rmtldiff_tr_comp_early_drop_uci= -rmstdiff_tr_comp_early_drop_uci
(70,808 missing values generated)

. gen rmtldiff_tr_comp_early_drop= -rmstdiff_tr_comp_early_drop
(70,807 missing values generated)

. gen rmtldiff_tr_comp_late_drop_lci= -rmstdiff_tr_comp_late_drop_lci
(70,808 missing values generated)

. gen rmtldiff_tr_comp_late_drop_uci= -rmstdiff_tr_comp_late_drop_uci
(70,808 missing values generated)

. gen rmtldiff_tr_comp_late_drop= -rmstdiff_tr_comp_late_drop
(70,807 missing values generated)

. gen rmtldiff_early_late_drop_lci= -rmstdiff_early_late_drop_lci
(70,808 missing values generated)

. gen rmtldiff_early_late_drop_uci= -rmstdiff_early_late_drop_uci
(70,808 missing values generated)

. gen rmtldiff_early_late_drop= -rmstdiff_early_late_drop
(70,807 missing values generated)

. 
. twoway  (rarea rmtldiff_tr_comp_early_drop_lci rmtldiff_tr_comp_early_drop_uci tt, color(gs2%35)) ///
>                  (line rmtldiff_tr_comp_early_drop tt, lcolor(gs2)) ///
>                 (rarea rmtldiff_tr_comp_late_drop_lci rmtldiff_tr_comp_late_drop_uci tt, color(gs6%35)) ///
>                  (line rmtldiff_tr_comp_late_drop tt, lcolor(gs6)) ///
>                 (rarea rmtldiff_early_late_drop_lci rmtldiff_early_late_drop_uci tt, color(gs10%35)) ///
>                  (line rmtldiff_early_late_drop tt, lcolor(gs10)) ///                            
>                                           (line zero tt, lcolor(black%20) lwidth(thick)) ///
>          , ylabel(, format(%3.1f)) ///
>          ytitle("Difference in RMTL (years)") ///
>          xtitle("Years from baseline treatment outcome") ///
>                  legend(order( 1 "Early vs. Tr. completion" 3 "Late vs. Tr. completion" 5 "Late vs. Early dropout") ring(0) pos(11) cols(1) region(lstyle(none)) region(c(non
> e)) nobox) ///
>                                  graphregion(color(white) lwidth(large)) bgcolor(white) ///
>                                  plotregion(fcolor(white)) graphregion(fcolor(white) ) /// //text(.5 1 "IR = <0.001") ///
>                  name(RMTLdiff, replace)
(note:  named style large not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)

. gr_edit .plotregion1.style.editstyle boxstyle(linestyle(color(none))) editcopy                           

. graph save "`c(pwd)'\_figs\h_m_ns_rp6_stdif_rmtl_m1.gph", replace
(file C:\Users\CISS Fondecyt\Mi unidad\Alvacast\SISTRAT 2022 (github)\_figs\h_m_ns_rp6_stdif_rmtl_m1.gph saved)

. graph export "`c(pwd)'\_figs\h_m_ns_rp6_stdif_rmtl_m1.pdf", as(pdf) replace 
(file C:\Users\CISS Fondecyt\Mi unidad\Alvacast\SISTRAT 2022 (github)\_figs\h_m_ns_rp6_stdif_rmtl_m1.pdf written in PDF format)

. use mariel_feb_23_2_m1.dta, clear 

. 
. cap noi drop rmst_h00 rmst_h11 rmst_h22
rmst_h00 ambiguous abbreviation

. 
. gen rmtldiff_tr_comp_early_drop_lci= -rmstdiff_tr_comp_early_drop_lci
(70,808 missing values generated)

. gen rmtldiff_tr_comp_early_drop_uci= -rmstdiff_tr_comp_early_drop_uci
(70,808 missing values generated)

. gen rmtldiff_tr_comp_early_drop= -rmstdiff_tr_comp_early_drop
(70,807 missing values generated)

. gen rmtldiff_tr_comp_late_drop_lci= -rmstdiff_tr_comp_late_drop_lci
(70,808 missing values generated)

. gen rmtldiff_tr_comp_late_drop_uci= -rmstdiff_tr_comp_late_drop_uci
(70,808 missing values generated)

. gen rmtldiff_tr_comp_late_drop= -rmstdiff_tr_comp_late_drop
(70,807 missing values generated)

. gen rmtldiff_early_late_drop_lci= -rmstdiff_early_late_drop_lci
(70,808 missing values generated)

. gen rmtldiff_early_late_drop_uci= -rmstdiff_early_late_drop_uci
(70,808 missing values generated)

. gen rmtldiff_early_late_drop= -rmstdiff_early_late_drop
(70,807 missing values generated)

. 
. twoway  (rarea rmtldiff_tr_comp_early_drop_lci rmtldiff_tr_comp_early_drop_uci tt, color(gs2%35)) ///
>                  (line rmtldiff_tr_comp_early_drop tt, lcolor(gs2)) ///
>                 (rarea rmtldiff_tr_comp_late_drop_lci rmtldiff_tr_comp_late_drop_uci tt, color(gs6%35)) ///
>                  (line rmtldiff_tr_comp_late_drop tt, lcolor(gs6)) ///
>                 (rarea rmtldiff_early_late_drop_lci rmtldiff_early_late_drop_uci tt, color(gs10%35)) ///
>                  (line rmtldiff_early_late_drop tt, lcolor(gs10)) ///                            
>                                           (line zero tt, lcolor(black%20) lwidth(thick)) ///
>          , ylabel(, format(%3.1f)) ///
>          ytitle("Difference in RMTL (years)") ///
>          xtitle("Years from baseline treatment outcome") ///
>                  legend(order( 1 "Early vs. Tr. completion" 3 "Late vs. Tr. completion" 5 "Late vs. Early dropout") ring(0) pos(11) cols(1) region(lstyle(none)) region(c(non
> e)) nobox) ///
>                                  graphregion(color(white) lwidth(large)) bgcolor(white) ///
>                                  plotregion(fcolor(white)) graphregion(fcolor(white) ) /// //text(.5 1 "IR = <0.001") ///
>                  name(RMTLdiff, replace)
(note:  named style large not found in class linewidth, default attributes used)
(note:  linewidth not found in scheme, default attributes used)

. gr_edit .plotregion1.style.editstyle boxstyle(linestyle(color(none))) editcopy                           

. graph save "`c(pwd)'\_figs\h_m_ns_rp6_stdif_rmtl_pris_m1.gph", replace
(file C:\Users\CISS Fondecyt\Mi unidad\Alvacast\SISTRAT 2022 (github)\_figs\h_m_ns_rp6_stdif_rmtl_pris_m1.gph saved)

. graph export "`c(pwd)'\_figs\h_m_ns_rp6_stdif_rmtl_pris_m1.pdf", as(pdf) replace 
(file C:\Users\CISS Fondecyt\Mi unidad\Alvacast\SISTRAT 2022 (github)\_figs\h_m_ns_rp6_stdif_rmtl_pris_m1.pdf written in PDF format)

Ended at= 17:47:37 27 May 2023

*#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#: *#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#: *#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:

Estimate time-specific survival probabilities & RMSTs

Condemnatory Sentence, Imputed

. use mariel_feb_23_m1.dta, clear 

. *qui estread using "mariel_feb_23_m1.sters"
. generate times = .
(70,863 missing values generated)

. replace times  = 1 if _n==1
(1 real change made)

. replace times = 3 if _n==2
(1 real change made)

. replace times = 5 if _n==3
(1 real change made)

. 
. * estimates replay m_nostag_rp8_tvc_1
. *1.994719
. 
. global covs_3b_pre_dum "mot_egr_early mot_egr_late tr_mod2 sex_dum2 edad_ini_cons esc1 esc2 sus_prin2 sus_prin3 sus_prin4 sus_prin5 fr_cons_sus_prin2 fr_cons_sus_prin3 fr_co
> ns_sus_prin4 fr_cons_sus_prin5 cond_ocu2 cond_ocu3 cond_ocu4 cond_ocu5 cond_ocu6 policonsumo num_hij2 tenviv1 tenviv2 tenviv4 tenviv5 mzone2 mzone3 n_off_vio n_off_acq n_off
> _sud n_off_oth psy_com2 dep2 rural2 rural3 porc_pobr susini2 susini3 susini4 susini5 ano_nac_corr cohab2 cohab3 cohab4 fis_com2 rc_x1 rc_x2 rc_x3"

. set seed 2125

. qui noi stpm2 $covs_3b_pre_dum , scale(hazard) df(8) eform tvc(mot_egr_early mot_egr_late) dftvc(1) 

Iteration 0:   log likelihood = -67564.521  
Iteration 1:   log likelihood =  -67542.98  
Iteration 2:   log likelihood = -67542.913  
Iteration 3:   log likelihood = -67542.913  

Log likelihood = -67542.913                     Number of obs     =     70,863

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |   1.745549   .0446049    21.80   0.000     1.660278    1.835199
         mot_egr_late |   1.584349   .0330964    22.03   0.000     1.520792    1.650563
              tr_mod2 |   1.219602   .0230072    10.52   0.000     1.175332    1.265539
             sex_dum2 |   .7371756   .0141314   -15.91   0.000     .7099924    .7653995
        edad_ini_cons |   .9880444    .001693    -7.02   0.000     .9847319    .9913682
                 esc1 |   1.156363   .0270577     6.21   0.000     1.104529     1.21063
                 esc2 |   1.105574   .0234113     4.74   0.000     1.060628    1.152425
            sus_prin2 |   1.073251   .0265018     2.86   0.004     1.022545    1.126471
            sus_prin3 |   1.409477   .0292487    16.54   0.000       1.3533    1.467985
            sus_prin4 |   1.042865    .032184     1.36   0.174     .9816548    1.107891
            sus_prin5 |   1.016235   .0648955     0.25   0.801       .89668     1.15173
    fr_cons_sus_prin2 |   .9371817   .0408175    -1.49   0.136     .8605003    1.020696
    fr_cons_sus_prin3 |   1.011526   .0357205     0.32   0.746     .9438831    1.084017
    fr_cons_sus_prin4 |   1.034831   .0383244     0.92   0.355     .9623778    1.112739
    fr_cons_sus_prin5 |    1.06922   .0377322     1.90   0.058     .9977659    1.145792
            cond_ocu2 |     1.0303   .0286058     1.08   0.282     .9757314     1.08792
            cond_ocu3 |   .9598899   .1248143    -0.31   0.753     .7439432     1.23852
            cond_ocu4 |   1.120973   .0368753     3.47   0.001     1.050979    1.195628
            cond_ocu5 |   1.258331   .0705362     4.10   0.000     1.127406     1.40446
            cond_ocu6 |   1.161962   .0190498     9.16   0.000     1.125218    1.199905
          policonsumo |   1.034928   .0201868     1.76   0.078     .9961091    1.075259
             num_hij2 |   1.156571   .0199469     8.43   0.000     1.118129    1.196335
              tenviv1 |   1.079807   .0648124     1.28   0.201     .9599641    1.214611
              tenviv2 |     1.0865    .041822     2.16   0.031     1.007546     1.17164
              tenviv4 |   1.054194     .02079     2.68   0.007     1.014224    1.095739
              tenviv5 |   1.010837   .0162774     0.67   0.503     .9794321    1.043249
               mzone2 |   1.284745   .0240226    13.40   0.000     1.238514    1.332702
               mzone3 |   1.423764   .0374035    13.45   0.000      1.35231    1.498994
            n_off_vio |   1.357781   .0240075    17.30   0.000     1.311533    1.405659
            n_off_acq |   1.808437   .0296752    36.11   0.000       1.7512    1.867545
            n_off_sud |   1.248557   .0214359    12.93   0.000     1.207243    1.291286
            n_off_oth |   1.353533   .0237068    17.28   0.000     1.307857    1.400804
             psy_com2 |   1.033938   .0200278     1.72   0.085     .9954198    1.073946
                 dep2 |   1.014232   .0173991     0.82   0.410     .9806974    1.048913
               rural2 |   1.023446   .0262531     0.90   0.366     .9732632    1.076217
               rural3 |   1.045232   .0294817     1.57   0.117     .9890172    1.104642
            porc_pobr |   1.293908   .1344832     2.48   0.013     1.055439    1.586258
              susini2 |   1.050942   .0313282     1.67   0.096     .9912991    1.114173
              susini3 |   1.144445   .0346367     4.46   0.000     1.078533    1.214386
              susini4 |   1.088176   .0175116     5.25   0.000      1.05439    1.123045
              susini5 |   1.141295    .052484     2.87   0.004     1.042927     1.24894
         ano_nac_corr |   .8804623   .0031804   -35.24   0.000     .8742509    .8867179
               cohab2 |   .9383804    .025249    -2.36   0.018     .8901754    .9891957
               cohab3 |   .9805971   .0319479    -0.60   0.548     .9199377    1.045256
               cohab4 |   .9252448    .024382    -2.95   0.003       .87867    .9742883
             fis_com2 |   1.043685   .0145983     3.06   0.002     1.015461    1.072693
                rc_x1 |   .8612007   .0041791   -30.79   0.000     .8530486    .8694307
                rc_x2 |   1.006862    .016198     0.43   0.671     .9756101    1.039116
                rc_x3 |   .9408644   .0387221    -1.48   0.139     .8679508    1.019903
                _rcs1 |   2.660346   .0355099    73.30   0.000      2.59165    2.730863
                _rcs2 |   1.112771   .0058371    20.37   0.000     1.101389     1.12427
                _rcs3 |   1.048769     .00387    12.90   0.000     1.041211    1.056381
                _rcs4 |   1.023972   .0024086    10.07   0.000     1.019262    1.028704
                _rcs5 |   1.014853   .0016169     9.25   0.000     1.011689    1.018027
                _rcs6 |    1.01101   .0012535     8.83   0.000     1.008556     1.01347
                _rcs7 |   1.007841   .0010724     7.34   0.000     1.005741    1.009945
                _rcs8 |   1.004565   .0009088     5.03   0.000     1.002785    1.006347
  _rcs_mot_egr_early1 |   .9075394   .0143514    -6.14   0.000     .8798427    .9361081
   _rcs_mot_egr_late1 |   .9430958   .0136912    -4.04   0.000     .9166396    .9703156
                _cons |   8.7e+109   6.3e+110    34.82   0.000     5.6e+103    1.3e+116
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. 
. stpm2_standsurv, at1(mot_egr_early 0 mot_egr_late 0) at2(mot_egr_early 1 mot_egr_late 0) timevar(times) rmst ci contrast(difference) ///
>      atvar(rmst_v_h0 rmst_v_h1) contrastvar(rmstdiff_tr_c_early_drop)

. 
. stpm2_standsurv, at1(mot_egr_early 0 mot_egr_late 0) at2(mot_egr_early 0 mot_egr_late 1) timevar(times ) rmst ci contrast(difference) ///
>      atvar(rmst_v_h00 rmst_v_h2) contrastvar(rmstdiff_tr_c_late_drop)

. 
. stpm2_standsurv, at1(mot_egr_early 1 mot_egr_late 0) at2(mot_egr_early 0 mot_egr_late 1) timevar(times ) rmst ci contrast(difference) ///
>      atvar(rmst_v_h11 rmst_v_h22) contrastvar(rmstdiff_erl_late_drop)   

. 
. set seed 2125

. qui noi stpm2 $covs_3b_pre_dum , scale(hazard) df(8) eform tvc(mot_egr_early mot_egr_late) dftvc(1) 

Iteration 0:   log likelihood = -67564.521  
Iteration 1:   log likelihood =  -67542.98  
Iteration 2:   log likelihood = -67542.913  
Iteration 3:   log likelihood = -67542.913  

Log likelihood = -67542.913                     Number of obs     =     70,863

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |   1.745549   .0446049    21.80   0.000     1.660278    1.835199
         mot_egr_late |   1.584349   .0330964    22.03   0.000     1.520792    1.650563
              tr_mod2 |   1.219602   .0230072    10.52   0.000     1.175332    1.265539
             sex_dum2 |   .7371756   .0141314   -15.91   0.000     .7099924    .7653995
        edad_ini_cons |   .9880444    .001693    -7.02   0.000     .9847319    .9913682
                 esc1 |   1.156363   .0270577     6.21   0.000     1.104529     1.21063
                 esc2 |   1.105574   .0234113     4.74   0.000     1.060628    1.152425
            sus_prin2 |   1.073251   .0265018     2.86   0.004     1.022545    1.126471
            sus_prin3 |   1.409477   .0292487    16.54   0.000       1.3533    1.467985
            sus_prin4 |   1.042865    .032184     1.36   0.174     .9816548    1.107891
            sus_prin5 |   1.016235   .0648955     0.25   0.801       .89668     1.15173
    fr_cons_sus_prin2 |   .9371817   .0408175    -1.49   0.136     .8605003    1.020696
    fr_cons_sus_prin3 |   1.011526   .0357205     0.32   0.746     .9438831    1.084017
    fr_cons_sus_prin4 |   1.034831   .0383244     0.92   0.355     .9623778    1.112739
    fr_cons_sus_prin5 |    1.06922   .0377322     1.90   0.058     .9977659    1.145792
            cond_ocu2 |     1.0303   .0286058     1.08   0.282     .9757314     1.08792
            cond_ocu3 |   .9598899   .1248143    -0.31   0.753     .7439432     1.23852
            cond_ocu4 |   1.120973   .0368753     3.47   0.001     1.050979    1.195628
            cond_ocu5 |   1.258331   .0705362     4.10   0.000     1.127406     1.40446
            cond_ocu6 |   1.161962   .0190498     9.16   0.000     1.125218    1.199905
          policonsumo |   1.034928   .0201868     1.76   0.078     .9961091    1.075259
             num_hij2 |   1.156571   .0199469     8.43   0.000     1.118129    1.196335
              tenviv1 |   1.079807   .0648124     1.28   0.201     .9599641    1.214611
              tenviv2 |     1.0865    .041822     2.16   0.031     1.007546     1.17164
              tenviv4 |   1.054194     .02079     2.68   0.007     1.014224    1.095739
              tenviv5 |   1.010837   .0162774     0.67   0.503     .9794321    1.043249
               mzone2 |   1.284745   .0240226    13.40   0.000     1.238514    1.332702
               mzone3 |   1.423764   .0374035    13.45   0.000      1.35231    1.498994
            n_off_vio |   1.357781   .0240075    17.30   0.000     1.311533    1.405659
            n_off_acq |   1.808437   .0296752    36.11   0.000       1.7512    1.867545
            n_off_sud |   1.248557   .0214359    12.93   0.000     1.207243    1.291286
            n_off_oth |   1.353533   .0237068    17.28   0.000     1.307857    1.400804
             psy_com2 |   1.033938   .0200278     1.72   0.085     .9954198    1.073946
                 dep2 |   1.014232   .0173991     0.82   0.410     .9806974    1.048913
               rural2 |   1.023446   .0262531     0.90   0.366     .9732632    1.076217
               rural3 |   1.045232   .0294817     1.57   0.117     .9890172    1.104642
            porc_pobr |   1.293908   .1344832     2.48   0.013     1.055439    1.586258
              susini2 |   1.050942   .0313282     1.67   0.096     .9912991    1.114173
              susini3 |   1.144445   .0346367     4.46   0.000     1.078533    1.214386
              susini4 |   1.088176   .0175116     5.25   0.000      1.05439    1.123045
              susini5 |   1.141295    .052484     2.87   0.004     1.042927     1.24894
         ano_nac_corr |   .8804623   .0031804   -35.24   0.000     .8742509    .8867179
               cohab2 |   .9383804    .025249    -2.36   0.018     .8901754    .9891957
               cohab3 |   .9805971   .0319479    -0.60   0.548     .9199377    1.045256
               cohab4 |   .9252448    .024382    -2.95   0.003       .87867    .9742883
             fis_com2 |   1.043685   .0145983     3.06   0.002     1.015461    1.072693
                rc_x1 |   .8612007   .0041791   -30.79   0.000     .8530486    .8694307
                rc_x2 |   1.006862    .016198     0.43   0.671     .9756101    1.039116
                rc_x3 |   .9408644   .0387221    -1.48   0.139     .8679508    1.019903
                _rcs1 |   2.660346   .0355099    73.30   0.000      2.59165    2.730863
                _rcs2 |   1.112771   .0058371    20.37   0.000     1.101389     1.12427
                _rcs3 |   1.048769     .00387    12.90   0.000     1.041211    1.056381
                _rcs4 |   1.023972   .0024086    10.07   0.000     1.019262    1.028704
                _rcs5 |   1.014853   .0016169     9.25   0.000     1.011689    1.018027
                _rcs6 |    1.01101   .0012535     8.83   0.000     1.008556     1.01347
                _rcs7 |   1.007841   .0010724     7.34   0.000     1.005741    1.009945
                _rcs8 |   1.004565   .0009088     5.03   0.000     1.002785    1.006347
  _rcs_mot_egr_early1 |   .9075394   .0143514    -6.14   0.000     .8798427    .9361081
   _rcs_mot_egr_late1 |   .9430958   .0136912    -4.04   0.000     .9166396    .9703156
                _cons |   8.7e+109   6.3e+110    34.82   0.000     5.6e+103    1.3e+116
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. 
. stpm2_standsurv, at1(mot_egr_early 0 mot_egr_late 0) at2(mot_egr_early 1 mot_egr_late 0) timevar(times) ci contrast(difference) ///
>      atvar(s_v_tr_comp s_v_early_drop) contrastvar(sdiff_v_tr_comp_early_drop)

. 
. stpm2_standsurv, at1(mot_egr_early 0 mot_egr_late 0) at2(mot_egr_early 0 mot_egr_late 1) timevar(times) ci contrast(difference) ///
>      atvar(s_v_tr_comp0 s_v_late_drop) contrastvar(sdiff_v_tr_comp_late_drop)

. 
. stpm2_standsurv, at1(mot_egr_early 1 mot_egr_late 0) at2(mot_egr_early 0 mot_egr_late 1) timevar(times) ci contrast(difference) ///
>      atvar(s_v_early_drop0 s_v_late_drop0) contrastvar(sdiff_v_early_late_drop) 

. *In https://fondecytacc.github.io/nDP/analisis_mariel_feb_2023_stata_m1.html
. *        mot_egr_early |    1.74308   .0445435    21.74   0.000     1.657926    1.832607
. 
. *After qui noi stpm2 here
. *        mot_egr_early |   1.745549   .0446049    21.80   0.000     1.660278    1.835199

. *list times rmst_v_h0 rmst_v_h0_lci rmst_v_h0_uci rmst_v_h1 rmst_v_h1_lci rmst_v_h1_uci rmst_v_h2 rmst_v_h2_lci rmst_v_h2_uci if !missing(times)
. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist s_v_tr_comp s_v_tr_comp_lci s_v_tr_comp_uci s_v_early_drop s_v_early_drop_lci s_v_early_drop_uci s_v_late_drop s_v_late_drop_lci s_v_late_drop_uci {
  2.                         scalar variable = "`var'"               
  3.                                         qui summarize `var' if inrange(times, .95, 1.05) // tolerance of .10
  4.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(times, 2.85, 3.15) // tolerance of .30
  6.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
  7.                                         qui summarize `var' if inrange(times,  4.85, 5.15) // tolerance of .30
  8.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
  9.          cap noi matrix ests_`var' = (`=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 10.          matrix colnames ests_`var' = `var'
 11.          matrix rownames ests_`var' = "1 yr" "3 yrs" "5 yrs"
 12.         }       

. 
. matrix est_as11m1_alt = (ests_s_v_tr_comp , ests_s_v_tr_comp_lci, ests_s_v_tr_comp_uci ,  ///
>         ests_s_v_early_drop , ests_s_v_early_drop_lci, ests_s_v_early_drop_uci , ///
>         ests_s_v_late_drop , ests_s_v_late_drop_lci , ests_s_v_late_drop_uci )

. matrix colnames est_as11m1_alt = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as11m1_alt) using "${pathdata2}prob_condsent_m1_main_alt.html", replace 
(output written to prob_condsent_m1_main_alt.html)

. 
.         
. 
. foreach var of varlist rmst_v_h0 rmst_v_h0_lci rmst_v_h0_uci rmst_v_h1 rmst_v_h1_lci rmst_v_h1_uci rmst_v_h2 rmst_v_h2_lci rmst_v_h2_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(times, .95, 1.05) // tolerance of .02
  4.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(times, 2.95, 3.05) // tolerance of .30
  6.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
  7.                                         qui summarize `var' if inrange(times,  4.95, 5.05) // tolerance of .30
  8.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
  9.          cap noi matrix ests_`var' = (`=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 10.          matrix colnames ests_`var' = `var'
 11.          matrix rownames ests_`var' = "1 yr" "3 yrs" "5 yrs"
 12.         }               

.         
. matrix est_as12m1_alt = (ests_rmst_v_h0 , ests_rmst_v_h0_lci , ests_rmst_v_h0_uci ,  ///
>         ests_rmst_v_h1 , ests_rmst_v_h1_lci , ests_rmst_v_h1_uci ,  ///
>         ests_rmst_v_h2 , ests_rmst_v_h2_lci , ests_rmst_v_h2_uci )

. matrix colnames est_as12m1_alt = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as12m1_alt) using "${pathdata2}rmst_condsent_m1_main_alt.html", replace        
(output written to rmst_condsent_m1_main_alt.html)

.          

. *sdiff_v_early_late_drop sdiff_v_tr_comp_late_drop  sdiff_v_tr_comp_early_drop
. local varlist "sdiff_v_tr_comp_early_drop sdiff_v_tr_comp_early_drop_lci sdiff_v_tr_comp_early_drop_uci sdiff_v_tr_comp_late_drop sdiff_v_tr_comp_late_drop_lci sdiff_v_tr_co
> mp_late_drop_uci sdiff_v_early_late_drop sdiff_v_early_late_drop_lci sdiff_v_early_late_drop_uci"

. foreach var of local varlist {
  2.     local newvar = subinstr("`var'", "_drop", "", .)
  3.     gen `newvar' = `var'
  4. }
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)

. 
. foreach var of varlist sdiff_v_tr_comp_early sdiff_v_tr_comp_early_lci sdiff_v_tr_comp_early_uci sdiff_v_tr_comp_late sdiff_v_tr_comp_late_lci sdiff_v_tr_comp_late_uci sdiff
> _v_early_late sdiff_v_early_late_lci sdiff_v_early_late_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(times, .95, 1.05) // tolerance of .10
  4.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(times, 2.95, 3.05) // tolerance of .30
  6.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
  7.                                         qui summarize `var' if inrange(times,  4.95, 5.05) // tolerance of .30
  8.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
  9.          cap noi matrix ests_`var' = ( `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 10.          matrix colnames ests_`var' = `var'
 11.          matrix rownames ests_`var' = "1 yr" "3 yrs" "5 yrs"
 12.                 }

.         
. matrix est_as14m1_alt = (ests_sdiff_v_tr_comp_early , ests_sdiff_v_tr_comp_early_lci , ests_sdiff_v_tr_comp_early_uci ,  ///
>         ests_sdiff_v_tr_comp_late , ests_sdiff_v_tr_comp_late_lci, ests_sdiff_v_tr_comp_late_uci , ///
>         ests_sdiff_v_early_late , ests_sdiff_v_early_late_lci , ests_sdiff_v_early_late_uci )

. matrix colnames est_as14m1_alt = "Comp vs Early" "Comp vs Early(lci)" "Comp vs Early(uci)" "Comp vs Late" "Comp vs Late (lci)" "Comp vs Late (uci)" "Early vs Late" "Early vs
>  Late (lci)" "Early vs Late (uci)"

. 
. esttab matrix(est_as14m1_alt) using "${pathdata2}prob_condsent_m1_main_diff_alt.html", replace 
(note: file prob_condsent_m1_main_diff_alt.html not found)
(output written to prob_condsent_m1_main_diff_alt.html)

. 

. local varlist "rmstdiff_tr_c_early_drop rmstdiff_tr_c_early_drop_lci rmstdiff_tr_c_early_drop_uci rmstdiff_tr_c_late_drop rmstdiff_tr_c_late_drop_lci rmstdiff_tr_c_late_drop
> _uci  rmstdiff_erl_late_drop rmstdiff_erl_late_drop_lci rmstdiff_erl_late_drop_uci"

. foreach var of local varlist {
  2.     local newvar = subinstr("`var'", "_drop", "", .)
  3.         local newvar = subinstr("`newvar'", "rmstdiff", "rmstd", .)
  4.     gen `newvar' = `var'
  5. }
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)

. 
. foreach var of varlist rmstd_tr_c_early rmstd_tr_c_early_lci rmstd_tr_c_early_uci rmstd_tr_c_late rmstd_tr_c_late_lci rmstd_tr_c_late_uci rmstd_erl_late rmstd_erl_late_lci r
> mstd_erl_late_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(times, .95, 1.05) // tolerance of .10
  4.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(times, 2.95, 3.05) // tolerance of .30
  6.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
  7.                                         qui summarize `var' if inrange(times,  4.95, 5.05) // tolerance of .30
  8.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
  9.          cap noi matrix ests_`var' = (`=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 10.          matrix colnames ests_`var' = `var'
 11.          matrix rownames ests_`var' = "1 yr" "3 yrs" "5 yrs"
 12.                 }

.         
. matrix est_as14m1_alt = (ests_rmstd_tr_c_early, ests_rmstd_tr_c_early_lci, ests_rmstd_tr_c_early_uci, ///
>                                         ests_rmstd_tr_c_late, ests_rmstd_tr_c_late_lci, ests_rmstd_tr_c_late_uci, ///
>                                         ests_rmstd_erl_late, ests_rmstd_erl_late_lci, ests_rmstd_erl_late_uci )

. matrix colnames est_as14m1_alt =  "Comp vs Early" "Comp vs Early(lci)" "Comp vs Early(uci)" "Comp vs Late" "Comp vs Late (lci)" "Comp vs Late (uci)" "Early vs Late" "Early v
> s Late (lci)" "Early vs Late (uci)"

. 
. esttab matrix(est_as14m1_alt) using "${pathdata2}rmst_condsent_m1_main_diff_alt.html", replace 
(note: file rmst_condsent_m1_main_diff_alt.html not found)
(output written to rmst_condsent_m1_main_diff_alt.html)

. 

Imprisonment, Imputed

. use mariel_feb_23_2_m1.dta, clear 

. *estread using "mariel_feb_23_2_m1.sters"
. 
. generate times = .
(70,863 missing values generated)

. replace times  = 1 if _n==1
(1 real change made)

. replace times = 3 if _n==2
(1 real change made)

. replace times = 5 if _n==3
(1 real change made)

. 
. global covs_3b_pre_dum "mot_egr_early mot_egr_late tr_mod2 sex_dum2 edad_ini_cons esc1 esc2 sus_prin2 sus_prin3 sus_prin4 sus_prin5 fr_cons_sus_prin2 fr_cons_sus_prin3 fr_co
> ns_sus_prin4 fr_cons_sus_prin5 cond_ocu2 cond_ocu3 cond_ocu4 cond_ocu5 cond_ocu6 policonsumo num_hij2 tenviv1 tenviv2 tenviv4 tenviv5 mzone2 mzone3 n_off_vio n_off_acq n_off
> _sud n_off_oth psy_com2 dep2 rural2 rural3 porc_pobr susini2 susini3 susini4 susini5 ano_nac_corr cohab2 cohab3 cohab4 fis_com2 rc_x1 rc_x2 rc_x3"

. 
. qui noi stpm2 $covs_3b_pre_dum , scale(hazard) df(6) eform tvc(mot_egr_early mot_egr_late) dftvc(1) 

Iteration 0:   log likelihood = -21774.145  
Iteration 1:   log likelihood = -21759.979  
Iteration 2:   log likelihood = -21759.872  
Iteration 3:   log likelihood = -21759.872  

Log likelihood = -21759.872                     Number of obs     =     70,863

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |   1.994852   .1087314    12.67   0.000     1.792731    2.219761
         mot_egr_late |   1.651233   .0777884    10.65   0.000     1.505598    1.810956
              tr_mod2 |   1.152116   .0429533     3.80   0.000     1.070932    1.239455
             sex_dum2 |   .5924607   .0255581   -12.13   0.000      .544427    .6447322
        edad_ini_cons |   .9734059   .0040331    -6.51   0.000     .9655331    .9813429
                 esc1 |   1.516986   .0833309     7.59   0.000     1.362145    1.689428
                 esc2 |   1.344025     .06934     5.73   0.000     1.214766    1.487037
            sus_prin2 |   1.195219   .0708791     3.01   0.003     1.064068    1.342535
            sus_prin3 |   1.716276   .0822599    11.27   0.000      1.56239    1.885318
            sus_prin4 |   1.142999   .0793454     1.93   0.054     .9975999    1.309589
            sus_prin5 |   1.354906   .1839488     2.24   0.025     1.038354     1.76796
    fr_cons_sus_prin2 |    .977386   .0969542    -0.23   0.818     .8046908    1.187143
    fr_cons_sus_prin3 |   .9957392   .0799293    -0.05   0.958     .8507824    1.165394
    fr_cons_sus_prin4 |   1.038108    .086308     0.45   0.653      .882011    1.221831
    fr_cons_sus_prin5 |    1.08905   .0865887     1.07   0.283     .9319019    1.272699
            cond_ocu2 |   1.087743   .0670889     1.36   0.173     .9638878    1.227513
            cond_ocu3 |   1.143944   .2800258     0.55   0.583       .70801     1.84829
            cond_ocu4 |   1.240744   .0810192     3.30   0.001     1.091691    1.410148
            cond_ocu5 |   1.332646   .1368113     2.80   0.005     1.089756    1.629673
            cond_ocu6 |   1.211739   .0420048     5.54   0.000     1.132146    1.296928
          policonsumo |   1.007253   .0431286     0.17   0.866     .9261719    1.095431
             num_hij2 |   1.136224   .0394231     3.68   0.000     1.061525     1.21618
              tenviv1 |   1.018513   .1150669     0.16   0.871     .8162099    1.270959
              tenviv2 |   1.068074   .0802883     0.88   0.381     .9217552     1.23762
              tenviv4 |   1.012196   .0420598     0.29   0.770      .933028    1.098082
              tenviv5 |   .9928354   .0331953    -0.22   0.830     .9298599    1.060076
               mzone2 |   1.416263   .0524875     9.39   0.000     1.317037    1.522965
               mzone3 |   1.544621   .0865199     7.76   0.000     1.384022    1.723855
            n_off_vio |   1.461835   .0503418    11.03   0.000     1.366423    1.563909
            n_off_acq |   2.796745   .0871343    33.01   0.000     2.631075    2.972847
            n_off_sud |   1.376993   .0456524     9.65   0.000     1.290361    1.469441
            n_off_oth |   1.702386   .0564758    16.04   0.000     1.595218    1.816754
             psy_com2 |   1.048481   .0402961     1.23   0.218     .9724036    1.130511
                 dep2 |   1.032711   .0387488     0.86   0.391     .9594905     1.11152
               rural2 |   .9370524   .0520279    -1.17   0.242     .8404322    1.044781
               rural3 |   .8649187    .054017    -2.32   0.020     .7652705    .9775424
            porc_pobr |   1.709119   .3691358     2.48   0.013     1.119256    2.609846
              susini2 |   1.097617   .0720002     1.42   0.156     .9651941    1.248208
              susini3 |   1.271345   .0731854     4.17   0.000     1.135701    1.423191
              susini4 |    1.15569   .0379013     4.41   0.000     1.083742    1.232415
              susini5 |   1.378443   .1164494     3.80   0.000       1.1681    1.626662
         ano_nac_corr |   .8465336   .0067735   -20.82   0.000     .8333613     .859914
               cohab2 |   .8633277   .0473393    -2.68   0.007     .7753563    .9612803
               cohab3 |    1.07592   .0686957     1.15   0.252     .9493631    1.219349
               cohab4 |   .9448006   .0518821    -1.03   0.301     .8483947    1.052162
             fis_com2 |   1.112992   .0326294     3.65   0.000     1.050843    1.178818
                rc_x1 |   .8447476   .0086673   -16.44   0.000     .8279298    .8619071
                rc_x2 |   .8807967   .0305094    -3.66   0.000      .822984    .9426706
                rc_x3 |   1.297611   .1196287     2.83   0.005     1.083106    1.554598
                _rcs1 |   2.177066   .0586595    28.87   0.000     2.065078    2.295126
                _rcs2 |   1.071884   .0075279     9.88   0.000     1.057231    1.086741
                _rcs3 |   1.033961   .0056547     6.11   0.000     1.022937    1.045104
                _rcs4 |   1.019485   .0038677     5.09   0.000     1.011932    1.027094
                _rcs5 |   1.012627   .0028211     4.50   0.000     1.007113    1.018171
                _rcs6 |    1.01034   .0021956     4.73   0.000     1.006046    1.014653
  _rcs_mot_egr_early1 |   .8978523   .0271955    -3.56   0.000     .8461013    .9527685
   _rcs_mot_egr_late1 |   .9205885   .0267904    -2.84   0.004     .8695497     .974623
                _cons |   7.4e+142   1.2e+144    20.43   0.000     1.5e+129    3.7e+156
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. 
. stpm2_standsurv, at1(mot_egr_early 0 mot_egr_late 0) at2(mot_egr_early 1 mot_egr_late 0) timevar(times) rmst ci contrast(difference) ///
>      atvar(rmst_v_h0 rmst_v_h1) contrastvar(rmstdiff_tr_c_early_drop)

. 
. stpm2_standsurv, at1(mot_egr_early 0 mot_egr_late 0) at2(mot_egr_early 0 mot_egr_late 1) timevar(times ) rmst ci contrast(difference) ///
>      atvar(rmst_v_h00 rmst_v_h2) contrastvar(rmstdiff_tr_c_late_drop)

. 
. stpm2_standsurv, at1(mot_egr_early 1 mot_egr_late 0) at2(mot_egr_early 0 mot_egr_late 1) timevar(times ) rmst ci contrast(difference) ///
>      atvar(rmst_v_h11 rmst_v_h22) contrastvar(rmstdiff_erl_late_drop)   

. 
. 
. qui noi stpm2 $covs_3b_pre_dum , scale(hazard) df(6) eform tvc(mot_egr_early mot_egr_late) dftvc(1) 

Iteration 0:   log likelihood = -21774.145  
Iteration 1:   log likelihood = -21759.979  
Iteration 2:   log likelihood = -21759.872  
Iteration 3:   log likelihood = -21759.872  

Log likelihood = -21759.872                     Number of obs     =     70,863

---------------------------------------------------------------------------------------
                      |     exp(b)   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
xb                    |
        mot_egr_early |   1.994852   .1087314    12.67   0.000     1.792731    2.219761
         mot_egr_late |   1.651233   .0777884    10.65   0.000     1.505598    1.810956
              tr_mod2 |   1.152116   .0429533     3.80   0.000     1.070932    1.239455
             sex_dum2 |   .5924607   .0255581   -12.13   0.000      .544427    .6447322
        edad_ini_cons |   .9734059   .0040331    -6.51   0.000     .9655331    .9813429
                 esc1 |   1.516986   .0833309     7.59   0.000     1.362145    1.689428
                 esc2 |   1.344025     .06934     5.73   0.000     1.214766    1.487037
            sus_prin2 |   1.195219   .0708791     3.01   0.003     1.064068    1.342535
            sus_prin3 |   1.716276   .0822599    11.27   0.000      1.56239    1.885318
            sus_prin4 |   1.142999   .0793454     1.93   0.054     .9975999    1.309589
            sus_prin5 |   1.354906   .1839488     2.24   0.025     1.038354     1.76796
    fr_cons_sus_prin2 |    .977386   .0969542    -0.23   0.818     .8046908    1.187143
    fr_cons_sus_prin3 |   .9957392   .0799293    -0.05   0.958     .8507824    1.165394
    fr_cons_sus_prin4 |   1.038108    .086308     0.45   0.653      .882011    1.221831
    fr_cons_sus_prin5 |    1.08905   .0865887     1.07   0.283     .9319019    1.272699
            cond_ocu2 |   1.087743   .0670889     1.36   0.173     .9638878    1.227513
            cond_ocu3 |   1.143944   .2800258     0.55   0.583       .70801     1.84829
            cond_ocu4 |   1.240744   .0810192     3.30   0.001     1.091691    1.410148
            cond_ocu5 |   1.332646   .1368113     2.80   0.005     1.089756    1.629673
            cond_ocu6 |   1.211739   .0420048     5.54   0.000     1.132146    1.296928
          policonsumo |   1.007253   .0431286     0.17   0.866     .9261719    1.095431
             num_hij2 |   1.136224   .0394231     3.68   0.000     1.061525     1.21618
              tenviv1 |   1.018513   .1150669     0.16   0.871     .8162099    1.270959
              tenviv2 |   1.068074   .0802883     0.88   0.381     .9217552     1.23762
              tenviv4 |   1.012196   .0420598     0.29   0.770      .933028    1.098082
              tenviv5 |   .9928354   .0331953    -0.22   0.830     .9298599    1.060076
               mzone2 |   1.416263   .0524875     9.39   0.000     1.317037    1.522965
               mzone3 |   1.544621   .0865199     7.76   0.000     1.384022    1.723855
            n_off_vio |   1.461835   .0503418    11.03   0.000     1.366423    1.563909
            n_off_acq |   2.796745   .0871343    33.01   0.000     2.631075    2.972847
            n_off_sud |   1.376993   .0456524     9.65   0.000     1.290361    1.469441
            n_off_oth |   1.702386   .0564758    16.04   0.000     1.595218    1.816754
             psy_com2 |   1.048481   .0402961     1.23   0.218     .9724036    1.130511
                 dep2 |   1.032711   .0387488     0.86   0.391     .9594905     1.11152
               rural2 |   .9370524   .0520279    -1.17   0.242     .8404322    1.044781
               rural3 |   .8649187    .054017    -2.32   0.020     .7652705    .9775424
            porc_pobr |   1.709119   .3691358     2.48   0.013     1.119256    2.609846
              susini2 |   1.097617   .0720002     1.42   0.156     .9651941    1.248208
              susini3 |   1.271345   .0731854     4.17   0.000     1.135701    1.423191
              susini4 |    1.15569   .0379013     4.41   0.000     1.083742    1.232415
              susini5 |   1.378443   .1164494     3.80   0.000       1.1681    1.626662
         ano_nac_corr |   .8465336   .0067735   -20.82   0.000     .8333613     .859914
               cohab2 |   .8633277   .0473393    -2.68   0.007     .7753563    .9612803
               cohab3 |    1.07592   .0686957     1.15   0.252     .9493631    1.219349
               cohab4 |   .9448006   .0518821    -1.03   0.301     .8483947    1.052162
             fis_com2 |   1.112992   .0326294     3.65   0.000     1.050843    1.178818
                rc_x1 |   .8447476   .0086673   -16.44   0.000     .8279298    .8619071
                rc_x2 |   .8807967   .0305094    -3.66   0.000      .822984    .9426706
                rc_x3 |   1.297611   .1196287     2.83   0.005     1.083106    1.554598
                _rcs1 |   2.177066   .0586595    28.87   0.000     2.065078    2.295126
                _rcs2 |   1.071884   .0075279     9.88   0.000     1.057231    1.086741
                _rcs3 |   1.033961   .0056547     6.11   0.000     1.022937    1.045104
                _rcs4 |   1.019485   .0038677     5.09   0.000     1.011932    1.027094
                _rcs5 |   1.012627   .0028211     4.50   0.000     1.007113    1.018171
                _rcs6 |    1.01034   .0021956     4.73   0.000     1.006046    1.014653
  _rcs_mot_egr_early1 |   .8978523   .0271955    -3.56   0.000     .8461013    .9527685
   _rcs_mot_egr_late1 |   .9205885   .0267904    -2.84   0.004     .8695497     .974623
                _cons |   7.4e+142   1.2e+144    20.43   0.000     1.5e+129    3.7e+156
---------------------------------------------------------------------------------------
Note: Estimates are transformed only in the first equation.

. 
. stpm2_standsurv, at1(mot_egr_early 0 mot_egr_late 0) at2(mot_egr_early 1 mot_egr_late 0) timevar(times) ci contrast(difference) ///
>      atvar(s_v_tr_comp s_v_early_drop) contrastvar(sdiff_v_tr_comp_early_drop)

. 
. stpm2_standsurv, at1(mot_egr_early 0 mot_egr_late 0) at2(mot_egr_early 0 mot_egr_late 1) timevar(times) ci contrast(difference) ///
>      atvar(s_v_tr_comp0 s_v_late_drop) contrastvar(sdiff_v_tr_comp_late_drop)

. 
. stpm2_standsurv, at1(mot_egr_early 1 mot_egr_late 0) at2(mot_egr_early 0 mot_egr_late 1) timevar(times) ci contrast(difference) ///
>      atvar(s_v_early_drop0 s_v_late_drop0) contrastvar(sdiff_v_early_late_drop) 

. *list times rmst_v_h0 rmst_v_h0_lci rmst_v_h0_uci rmst_v_h1 rmst_v_h1_lci rmst_v_h1_uci rmst_v_h2 rmst_v_h2_lci rmst_v_h2_uci if !missing(times)
. 
. *sdiff_tr_comp_early_drop sdiff_tr_comp_late_drop sdiff_early_late_drop
. foreach var of varlist s_v_tr_comp s_v_tr_comp_lci s_v_tr_comp_uci s_v_early_drop s_v_early_drop_lci s_v_early_drop_uci s_v_late_drop s_v_late_drop_lci s_v_late_drop_uci {
  2.                         scalar variable = "`var'"               
  3.                                         qui summarize `var' if inrange(times, .95, 1.05) // tolerance of .10
  4.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(times, 2.85, 3.15) // tolerance of .30
  6.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
  7.                                         qui summarize `var' if inrange(times,  4.85, 5.15) // tolerance of .30
  8.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
  9.          cap noi matrix ests_`var' = (`=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 10.          matrix colnames ests_`var' = `var'
 11.          matrix rownames ests_`var' = "1 yr" "3 yrs" "5 yrs"
 12.         }       

. 
. matrix est_as21m1_alt = (ests_s_v_tr_comp , ests_s_v_tr_comp_lci, ests_s_v_tr_comp_uci ,  ///
>         ests_s_v_early_drop , ests_s_v_early_drop_lci, ests_s_v_early_drop_uci , ///
>         ests_s_v_late_drop , ests_s_v_late_drop_lci , ests_s_v_late_drop_uci )

. matrix colnames est_as21m1_alt = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as21m1_alt) using "${pathdata2}prob_prison_m1_main_alt.html", replace 
(output written to prob_prison_m1_main_alt.html)

. 
.         
. 
. foreach var of varlist rmst_v_h0 rmst_v_h0_lci rmst_v_h0_uci rmst_v_h1 rmst_v_h1_lci rmst_v_h1_uci rmst_v_h2 rmst_v_h2_lci rmst_v_h2_uci {
  2.                         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(times, .95, 1.05) // tolerance of .02
  4.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(times, 2.95, 3.05) // tolerance of .30
  6.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
  7.                                         qui summarize `var' if inrange(times,  4.95, 5.05) // tolerance of .30
  8.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
  9.          cap noi matrix ests_`var' = (`=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 10.          matrix colnames ests_`var' = `var'
 11.          matrix rownames ests_`var' = "1 yr" "3 yrs" "5 yrs"
 12.         }               

.         
. matrix est_as22m1_alt = (ests_rmst_v_h0 , ests_rmst_v_h0_lci , ests_rmst_v_h0_uci ,  ///
>         ests_rmst_v_h1 , ests_rmst_v_h1_lci , ests_rmst_v_h1_uci ,  ///
>         ests_rmst_v_h2 , ests_rmst_v_h2_lci , ests_rmst_v_h2_uci )

. matrix colnames est_as22m1_alt = Comp Comp_lci Comp_uci Early Early_lci Early_uci Late Late_lci Late_uci 

. 
. esttab matrix(est_as22m1_alt) using "${pathdata2}rmst_prison_m1_main_alt.html", replace          
(output written to rmst_prison_m1_main_alt.html)

.          

. *sdiff_v_early_late_drop sdiff_v_tr_comp_late_drop  sdiff_v_tr_comp_early_drop
. local varlist "sdiff_v_tr_comp_early_drop sdiff_v_tr_comp_early_drop_lci sdiff_v_tr_comp_early_drop_uci sdiff_v_tr_comp_late_drop sdiff_v_tr_comp_late_drop_lci sdiff_v_tr_co
> mp_late_drop_uci sdiff_v_early_late_drop sdiff_v_early_late_drop_lci sdiff_v_early_late_drop_uci"

. foreach var of local varlist {
  2.     local newvar = subinstr("`var'", "_drop", "", .)
  3.     gen `newvar' = `var'
  4. }
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)

. 
. foreach var of varlist sdiff_v_tr_comp_early sdiff_v_tr_comp_early_lci sdiff_v_tr_comp_early_uci sdiff_v_tr_comp_late sdiff_v_tr_comp_late_lci sdiff_v_tr_comp_late_uci sdiff
> _v_early_late sdiff_v_early_late_lci sdiff_v_early_late_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(times, .95, 1.05) // tolerance of .10
  4.                                         scalar e1y_`var' = round(round(r(mean),.001)*100,.1)
  5.                                         qui summarize `var' if inrange(times, 2.95, 3.05) // tolerance of .30
  6.                                         scalar e3y_`var' = round(round(r(mean),.001)*100,.1)
  7.                                         qui summarize `var' if inrange(times,  4.95, 5.05) // tolerance of .30
  8.                                         scalar e5y_`var' = round(round(r(mean),.001)*100,.1)
  9.          cap noi matrix ests_`var' = ( `=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 10.          matrix colnames ests_`var' = `var'
 11.          matrix rownames ests_`var' = "1 yr" "3 yrs" "5 yrs"
 12.                 }

.         
. matrix est_as23m1_alt = (ests_sdiff_v_tr_comp_early , ests_sdiff_v_tr_comp_early_lci , ests_sdiff_v_tr_comp_early_uci ,  ///
>         ests_sdiff_v_tr_comp_late , ests_sdiff_v_tr_comp_late_lci, ests_sdiff_v_tr_comp_late_uci , ///
>         ests_sdiff_v_early_late , ests_sdiff_v_early_late_lci , ests_sdiff_v_early_late_uci )

. matrix colnames est_as23m1_alt = "Comp vs Early" "Comp vs Early(lci)" "Comp vs Early(uci)" "Comp vs Late" "Comp vs Late (lci)" "Comp vs Late (uci)" "Early vs Late" "Early vs
>  Late (lci)" "Early vs Late (uci)"

. 
. esttab matrix(est_as23m1_alt) using "${pathdata2}prob_prison_m1_main_diff_alt.html", replace 
(output written to prob_prison_m1_main_diff_alt.html)

. 

. local varlist "rmstdiff_tr_c_early_drop rmstdiff_tr_c_early_drop_lci rmstdiff_tr_c_early_drop_uci rmstdiff_tr_c_late_drop rmstdiff_tr_c_late_drop_lci rmstdiff_tr_c_late_drop
> _uci  rmstdiff_erl_late_drop rmstdiff_erl_late_drop_lci rmstdiff_erl_late_drop_uci"

. foreach var of local varlist {
  2.     local newvar = subinstr("`var'", "_drop", "", .)
  3.         local newvar = subinstr("`newvar'", "rmstdiff", "rmstd", .)
  4.     gen `newvar' = `var'
  5. }
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)
(70,860 missing values generated)

. 
. foreach var of varlist rmstd_tr_c_early rmstd_tr_c_early_lci rmstd_tr_c_early_uci rmstd_tr_c_late rmstd_tr_c_late_lci rmstd_tr_c_late_uci rmstd_erl_late rmstd_erl_late_lci r
> mstd_erl_late_uci {
  2.         scalar variable = "`var'"
  3.                                         qui summarize `var' if inrange(times, .95, 1.05) // tolerance of .10
  4.                                         scalar e1y_`var' = round(round(r(mean),.0001),.001)
  5.                                         qui summarize `var' if inrange(times, 2.95, 3.05) // tolerance of .30
  6.                                         scalar e3y_`var' = round(round(r(mean),.0001),.001)
  7.                                         qui summarize `var' if inrange(times,  4.95, 5.05) // tolerance of .30
  8.                                         scalar e5y_`var' = round(round(r(mean),.0001),.001)
  9.          cap noi matrix ests_`var' = (`=scalar(e1y_`var')'\ `=scalar(scalar(e3y_`var'))'\ `=scalar(scalar(e5y_`var'))')
 10.          matrix colnames ests_`var' = `var'
 11.          matrix rownames ests_`var' = "1 yr" "3 yrs" "5 yrs"
 12.                 }

.         
. matrix est_as24m1_alt = (ests_rmstd_tr_c_early, ests_rmstd_tr_c_early_lci, ests_rmstd_tr_c_early_uci, ///
>                                         ests_rmstd_tr_c_late, ests_rmstd_tr_c_late_lci, ests_rmstd_tr_c_late_uci, ///
>                                         ests_rmstd_erl_late, ests_rmstd_erl_late_lci, ests_rmstd_erl_late_uci )

. matrix colnames est_as24m1_alt =  "Comp vs Early" "Comp vs Early(lci)" "Comp vs Early(uci)" "Comp vs Late" "Comp vs Late (lci)" "Comp vs Late (uci)" "Early vs Late" "Early v
> s Late (lci)" "Early vs Late (uci)"

. 
. esttab matrix(est_as24m1_alt) using "${pathdata2}rmst_prison_m1_main_diff_alt.html", replace 
(output written to rmst_prison_m1_main_diff_alt.html)

.