Methods for Analysis of Pre-Post Data in Clinical Research: A Comparison of Five Common Methods.

ABSTRACT: Often repeated measures data are summarized into pre-post-treatment measurements. Various methods exist in the literature for estimating and testing treatment effect, including ANOVA, analysis of covariance (ANCOVA), and linear mixed modeling (LMM). Under the first two methods, outcomes can either be modeled as the post treatment measurement (ANOVA-POST or ANCOVA-POST), or a change score between pre and post measurements (ANOVA-CHANGE, ANCOVA-CHANGE). In LMM, the outcome is modeled as a vector of responses with or without Kenward-Rogers adjustment. We consider five methods common in the literature, and discuss them in terms of supporting simulations and theoretical derivations of variance. Consistent with existing literature, our results demonstrate that each method leads to unbiased treat

SUBMITTER: O'Connell NS 

PROVIDER: S-EPMC6290914 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature