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：近年来，多种统计方法已用于研究双边数据中的组内相关性。在实际应用中，通过某些控制变量对双边数据进行分层，能够提供更复杂的统计结果，以满足随机临床试验中不同研究的需求。本文在等相关性假设下，提出了三种检验统计量（似然比检验、得分检验和Wald型检验统计量），用于评估分层双边相关数据中比例比的同质性。通过蒙特卡洛模拟检验第一类错误和统计功效，结果表明基于经验第一类错误和效力，得分检验产生了稳健的结果。最后，通过一个实际数据示例对三种检验方法进行了说明。