Current issues with covariate adjustment in the analysis of data from randomized controlled trials.
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.
Alemayehu
Demissie
D
Clinical Affairs, Pfizer, Inc., New York City, NY 10017, USA. alemad@pfizer.com
D000704:Analysis of Variance; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012107:Research Design