Intraclass correlation in bilateral data has been investigated in recent decades with various statistical methods. In practice, stratifying bilateral data by some control variables will provide more sophisticated statistical results to satisfy different research proposed in random clinical trials. In this article, we propose three test statistics (likelihood ratio test, score test, and Wald-type test statistics) to evaluate the homogeneity of proportion ratios for stratified bilateral correlated data under an equal correlation assumption. Monte Carlo simulations of Type I error and power are performed, and the score test yields a robust outcome based on empirical Type I error and power. Lastly, a real data example is conducted to illustrate the proposed three tests.
翻译:在过去的几十年中,随机临床试验中双边数据的班级内相关性已经得到了各种统计方法的研究。实践中,将双边数据通过某些控制变量进行分层会提供更复杂的统计结果,以满足不同的研究目的。在本文中,我们提出了三种检验统计量(似然比检验,得分检验和Wald-type检验统计量),以在相等相关性假设下评估分层双边相关数据的比例比的均匀性。进行了Monte Carlo模拟以检验类型I误差和功率,并且根据实际类型I误差和功率,得分检验产生了稳健的结果。最后,进行了一个真实数据例子来说明所提出的三个测试。