In clinical trials studying paired parts of a subject with binary outcomes, it is expected to collect measurements bilaterally. However, there are cases where subjects contribute measurements for only one part. By utilizing combined data, it is possible to gain additional information compared to using bilateral or unilateral data alone. With the combined data, this article investigates homogeneity tests of risk differences with the presence of stratification effects and proposes interval estimations of a common risk difference if stratification does not introduce underlying dissimilarities. Under Dallal's model \citeyearpar{dallal1988paired}, we propose three test statistics and evaluate their performances regarding type I error controls and powers. Confidence intervals of a common risk difference with satisfactory coverage probabilities and interval length are constructed. Our simulation results show that the score test is the most robust and the profile likelihood confidence interval outperforms other methods proposed. Data from a study of acute otitis media is used to illustrate our proposed procedures.

翻译：在针对受试者配对部位进行二元结局分析的临床试验中，通常期望采集双侧测量数据。然而，实际研究中常出现受试者仅提供单侧测量值的情况。通过整合双侧与单侧数据，相较于单独使用其中一类数据可获得更多信息。基于合并数据，本文研究了存在分层效应时风险差异的同质性检验，并提出当分层未引入潜在异质性时共同风险差异的区间估计方法。在Dallal模型框架下\citeyearpar{dallal1988paired}，我们构建了三种检验统计量，并从第一类错误控制与检验效能角度评估其性能。同时构建了具有满意覆盖率与区间长度的共同风险差异置信区间。模拟结果表明，得分检验最为稳健，而轮廓似然置信区间优于其他方法。最后通过急性中耳炎研究数据验证了所提方法的实用性。