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Implementing Propensity Score Matching Estimators with …

1 Implementing Propensity Score Matching Estimatorswith STATAB arbara SianesiUniversity College LondonandInstitute for Fiscal StudiesE-mail: forUK Stata Users Group, VII MeetingLondon, May 2001 2 BACKGROUND: THE EVALUATION PROBLEMPOTENTIAL-OUTCOME APPROACHE valuating the causal effect of some treatment on some outcome Yexperienced by units in the population of the outcome of unit i if i were exposed to the treatmentY0i the outcome of unit i if i were not exposed to the treatmentDi {0, 1} indicator of the treatment actually received by unit iYi = Y0i + Di (Y1i Y0i)

IMPLEMENTING PROPENSITY SCORE MATCHING ESTIMATORS WITH STATA Preparing the dataset Keep only one observation per individual Estimate the propensity score on the X’s e.g. via probit or logit and retrieve either the predicted probability or the index Necessary variables: the 1/0 dummy variable identifying the treated/controls the predicted ...

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Propensity Score Matching Regression …

fmwww.bc.edu

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Some Practical Guidance for the Implementation of ...

ftp.iza.org

Propensity Score Estimation (sec. 3.1) Step 2: Choose Matching Algorithm (sec. 3.2) Step 3: Check Over-lap/Common Support (sec. 3.3) Step 5: Sensitivity Analysis (sec. 4) Step 4: Matching Quality/Effect Estimation (sec. 3.4-3.7) CVM: Covariate Matching, PSM: Propensity Score Matching The aim of this paper is to discuss these issues and give ...

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support.sas.com

"Analysis of Observational Health Care Data Using SAS®", which is published by the SAS Institute, is used to analyze how a health care treatment impacted an associated health care outcome. It details how propensity scores are created and how propensity score matching is used to balance covariates between treated and untreated observations.

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raymarshallcenter.org

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www.hcp.med.harvard.edu

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www.unicef-irc.org

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