Affiliation:
1. Institute of Applied Health Research University of Birmingham Birmingham UK
2. College of Medicine University of Ibadan Ibadan Oyo State Nigeria
Abstract
In this article, we derive and compare methods to derive P‐values and sets of confidence intervals with strong control of the family‐wise error rates and coverage for estimates of treatment effects in cluster randomized trials with multiple outcomes. There are few methods for P‐value corrections and deriving confidence intervals, limiting their application in this setting. We discuss the methods of Bonferroni, Holm, and Romano and Wolf and adapt them to cluster randomized trial inference using permutation‐based methods with different test statistics. We develop a novel search procedure for confidence set limits using permutation tests to produce a set of confidence intervals under each method of correction. We conduct a simulation‐based study to compare family‐wise error rates, coverage of confidence sets, and the efficiency of each procedure in comparison to no correction using both model‐based standard errors and permutation tests. We show that the Romano‐Wolf type procedure has nominal error rates and coverage under non‐independent correlation structures and is more efficient than the other methods in a simulation‐based study. We also compare results from the analysis of a real‐world trial.
Funder
Medical Research Council Canada
National Institute for Health and Care Research
Subject
Statistics and Probability,Epidemiology
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献