ITPSCORE: Stata module to implement Iterative Propensity Score Logistic Regression Model Search Procedure

Ravaris Moore (), Jennie E. Brand () and Tanvi Shinkre ()
Additional contact information
Ravaris Moore: Princeton University
Jennie E. Brand: UCLA
Tanvi Shinkre: UCLA

Statistical Software Components from Boston College Department of Economics

Abstract: itpscore performs the iterative propensity score logistic regression model search procedure described by Imbens and Rubin (2015). Given a binary outcome measure and a list of candidate explanatory variables, the program iteratively selects explanatory variables for inclusion into a propensity score model based upon changes in the logistic regression log-likelihood. The program also produces multiplicative interactions (and second order terms) of all explanatory variables selected for model inclusion and treats interaction terms as additional candidate covariates. The package accommodates user defined convergence thresholds and the option to specify a set of explanatory variables for default model inclusion. The resulting propensity score model supports propensity score matching techniques, methods utilizing propensity scores to control for endogenous selection, and methods utilizing propensity scores in the estimation of heterogenous treatment effects.

Language: Stata
Requires: Stata version 17
Keywords: propensity score; logit; logistic regression (search for similar items in EconPapers)
Date: 2021-11-21, Revised 2021-11-24
Note: This module should be installed from within Stata by typing "ssc install itpscore". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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http://fmwww.bc.edu/repec/bocode/i/itpscore.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/i/itpscore.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/i/itpscore_pdf_supplement.pdf documentation (application/pdf)

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