Causal inference using STATA

This work has two main objectives: first to provide a short overview of available analytical methods that estimate Causal Effect measures when “association is not causation” and then to introduce a set of programs which estimate them. The methods used are: Outcome Regression adjustment, Inverse Weig...

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Autor principal: Soto, María Cecilia
Otros Autores: Rotnitzky, Andrea
Formato: Tesis de maestría acceptedVersion
Lenguaje:Español
Publicado: Universidad Torcuato Di Tella 2017
Materias:
Estadística > Modelos econométricos
Statistics > Econometric models
Tesis
Acceso en línea:http://repositorio.utdt.edu/handle/utdt/1334
Aporte de:
Repositorio Digital Universidad Torcuato Di Tella de Universidad Torcuato Di Tella
id I57-R16320.500.13098-1334
record_format dspace
institution Universidad Torcuato Di Tella
institution_str I-57
repository_str R-163
collection Repositorio Digital Universidad Torcuato Di Tella
language Español
orig_language_str_mv spa
topic Estadística -- Modelos econométricos
Statistics -- Econometric models
Tesis
spellingShingle Estadística -- Modelos econométricos
Statistics -- Econometric models
Tesis
Soto, María Cecilia
Causal inference using STATA
description This work has two main objectives: first to provide a short overview of available analytical methods that estimate Causal Effect measures when “association is not causation” and then to introduce a set of programs which estimate them. The methods used are: Outcome Regression adjustment, Inverse Weighted probability, Double Robust bounded and Stratification by the propensity score. In order to implement such methods we have developed five programs using STATA software for both continuous and binary outcomes. When the outcome variable is binary the programs outputs estimators of the Average Treatment effect (ATE), the Causal Risk ratio (CCR) and the Causal Odd ratio (COR) while if the outcome variable is continuous it only outputs the ATE. In addition we constructed a special program (prop_score.ado) for the evaluation of the propensity score fit in order to use it in the propensity score stratification method. These programs are: t_out_reg.ado, t_ipw.ado, t_prop_stat.ado, the dr_bounded.ado and the t_prop_score.ado.
author2 Rotnitzky, Andrea
author_facet Rotnitzky, Andrea
Soto, María Cecilia
format Tesis de maestría
acceptedVersion
author Soto, María Cecilia
author_sort Soto, María Cecilia
title Causal inference using STATA
title_short Causal inference using STATA
title_full Causal inference using STATA
title_fullStr Causal inference using STATA
title_full_unstemmed Causal inference using STATA
title_sort causal inference using stata
publisher Universidad Torcuato Di Tella
publishDate 2017
url http://repositorio.utdt.edu/handle/utdt/1334
work_keys_str_mv AT sotomariacecilia causalinferenceusingstata
bdutipo_str Repositorios
_version_ 1764820542925307908

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