More powerful two-sample tests for differences in repeated measures of adverse effects in psychiatric trials when only some patients may be at risk

Abstract

Common adverse effect measures in psychiatric trials are typically analysed with repeated measures ANOVA, despite having distributions which violate key assumptions of that method; moreover, some adverse effects may be concentrated in vulnerable subgroups of participants. For testing treatment differences in adverse effects, we propose use of Kendall's taub as a summary measure of within-participant trends in adverse events, in conjunction with a weighted modification of a rank test proposed by Conover and Salsburg. Data on extrapyramidal side effects from a controlled clinical trial conducted in persons with treatment resistant schizophrenia was used to compare the proposed analysis to repeated measures ANOVA using mixed models and alternate tests for treatment differences in taub trend scores.