Statistical Models Commons^™

Comparing Paired Vs. Non-Paired Statistical Methods Of Analyses When Making Inferences About Absolute Risk Reductions In Propensity-Score Matched Samples., Peter C. Austin

Peter Austin

Propensity-score matching allows one to reduce the effects of treatment-selection bias or confounding when estimating the effects of treatments when using observational data. Some authors have suggested that methods of inference appropriate for independent samples can be used for assessing the statistical significance of treatment effects when using propensity-score matching. Indeed, many authors in the applied medical literature use methods for independent samples when making inferences about treatment effects using propensity-score matched samples. Dichotomous outcomes are common in healthcare research. In this study, we used Monte Carlo simulations to examine the effect on inferences about risk differences (or absolute risk …