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Testing homogeneity of proportion ratios for stratified correlated bilateral data in two-arm randomized clinical trials

机译:在两组随机临床试验中测试分层相关双侧数据的比例比的同质性

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摘要

Stratified data analysis is an important research topic in many biomedical studies and clinical trials. In this article, we develop five test statistics for testing the homogeneity of proportion ratios for stratified correlated bilateral binary data based on an equal correlation model assumption. Bootstrap procedures based on these test statistics are also considered. To evaluate the performance of these statistics and procedures, we conduct Monte Carlo simulations to study their empirical sizes and powers under various scenarios. Our results suggest that the procedure based on score statistic performs well generally and is highly recommended. When the sample size is large, procedures based on the commonly used weighted least square estimate and logarithmic transformation with Mantel-Haenszel estimate are recommended as they do not involve any computation of maximum likelihood estimates requiring iterative algorithms. We also derive approximate sample size formulas based on the recommended test procedures. Finally, we apply the proposed methods to analyze a multi-center randomized clinical trial for scleroderma patients.
机译:分层数据分析是许多生物医学研究和临床试验中的重要研究课题。在本文中,我们基于相等的相关性模型假设,开发了五个检验统计数据,用于检验分层相关的双边二元数据的比例比率的同质性。还考虑了基于这些测试统计信息的引导程序。为了评估这些统计数据和程序的性能,我们进行了蒙特卡洛模拟,以研究它们在各种情况下的经验规模和功效。我们的结果表明,基于评分统计的程序通常表现良好,因此强烈建议使用。当样本量很大时,建议使用基于常用加权最小二乘估计和具有Mantel-Haenszel估计的对数变换的过程,因为它们不涉及需要迭代算法的最大似然估计的任何计算。我们还会根据建议的测试程序得出近似的样本量公式。最后,我们将提出的方法用于硬皮病患者的多中心随机临床试验分析。

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