MIESIZE: Stata module to estimate effect sizes from multiply imputed data

Paul A Tiffin ()
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Paul A Tiffin: Department of Health Sciences, University of York

Statistical Software Components from Boston College Department of Economics

Abstract: miesize is a Stata program which calculates effect sizes for a binary variable from multiply imputed data in wide format. The estimates and standard errors (used to calculate the confidence intervals) are recombined using Rubin's rules (Rubin 2004). These rules are applied such that the average point estimate for the effect size is calculated from the imputed datasets. The pooled standard error, and hence 95% confidence intervals, are calculated in such a way that accounts for both variance between the imputed datasets, as well as the variance within them. Pooled effect-sizes and confidence intervals for Cohen's d (Cohen 1988), Hedges' g (Hedges 1981) and Glass' Delta (Smith and Glass 1977) are given.

Language: Stata
Requires: Stata version 15
Keywords: effect size; multiple imputation (search for similar items in EconPapers)
Date: 2023-02-12, Revised 2024-04-29
Note: This module should be installed from within Stata by typing "ssc install miesize". 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/m/miesize.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/m/miesize.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/m/miesize_validation_do_v15.do sample do-file (text/plain)

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