title: Testing homogeneity of the risk ratio in stratified noncompliance randomized trials.
abstract: The risk ratio (RR), defined as the ratio of probabilities of having an adverse event between an experimental treatment and a control treatment, is one of the most commonly used indices to measure the efficacy of an experimental treatment in a randomized clinical trial (RCT). When we want to obtain a summary estimator of the RR in stratified analysis, it is important that we can examine the assumption whether the underlying RR varies between strata. Although we can find a few publications on testing the homogeneity of RR, all these papers focus the ideal situation in which every patient complies with his/her assigned treatment. The research on testing the homogeneity of RR for a noncompliance RCT is limited. In this paper, we develop three simple test statistics for testing homogeneity of the RR under a noncompliance stratified RCT with large strata. To evaluate the performance of these statistics, we apply Monte Carlo simulation to calculate Type I error and power in a variety of situations. Based on the findings, we provide a general guideline of selecting a preferable test statistic under various situations. Finally, we include a large field trial studying the effect of a multifactor intervention program on the mortality of coronary heart disease (CHD) in middle-aged men to illustrate the practical use of these test statistics.
authors.affiliation: Department of Mathematics and Statistics, College of Sciences, San Diego State University, San Diego, CA 92182-7720, USA. kjl@rohan.sdsu.edu
authors.forename: Kung-Jong
authors.initials: KJ
authors.lastname: Lui
mesh_terms: D003327:Coronary Disease / Q000453:epidemiology; D003627:Data Interpretation, Statistical; D006801:Humans; D008297:Male; D008875:Middle Aged; D009010:Monte Carlo Method; D016017:Odds Ratio; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D016312:Treatment Refusal / Q000706:statistics & numerical data*