RWRMED: Stata module for performing causal mediation analysis using regression-with-residuals

Ariel Linden, Chuck Huber () and Geoffrey T. Wodtke ()
Additional contact information
Chuck Huber: StataCorp
Geoffrey T. Wodtke: University of Chicago

Statistical Software Components from Boston College Department of Economics

Abstract: rwrmed performs causal mediation analysis using regression-with-residuals. Using gsem, two models are estimated: a model for the mediator conditional on treatment and the pre-treatment covariates (if specified) after centering them around their sample means, and a model for the outcome conditional on treatment, the mediator, the pre-treatment covariates (if specified) after centering them around their sample means, and the post-treatment covariates (if specified) after centering them around their estimated conditional means given all prior variables. Thus rwrmed allows for the presence of treatment-induced confounders, which are post-treatment covariates that confound the mediator-outcome relationship.

Language: Stata
Requires: Stata version 14
Keywords: causal inference; mediation analysis; indirect effects; direct effects (search for similar items in EconPapers)
Date: 2020-06-27, Revised 2021-04-03
Note: This module should be installed from within Stata by typing "ssc install rwrmed". 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/r/rwrmed.ado program code (text/plain)
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http://fmwww.bc.edu/repec/bocode/r/rwrmed.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/d/depression.dta sample data file (application/x-stata)

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