Current issues with covariate adjustment in the analysis of data from randomized controlled trials
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Updated: Jun 19, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
1Clinical Affairs, Pfizer, Inc., New York City, NY 10017, USA. alemad@pfizer.com
Abstract:
Covariate adjustment helps to minimize bias by eliminating the influence of one variable on another and generally improves precision of estimators in comparative studies. However, despite considerable discussion in the literature on the topic, there is continued controversy and misunderstanding about its valid use and impact in medical research. We review current issues and suggest steps to be taken in the course of the design, analysis, and reporting of studies to further heighten awareness of the problem particularly among nonstatisticians. It is reemphasized that prespecification of the variables of interest and parsimony of the analytical models are essential elements for valid use and interpretation of results of analysis involving covariates.
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