组合单侧和双侧数据的适合度检验

涉及成对器官的临床试验常常产生单侧和双侧数据混合的情况，即每个受试者可能在特定情况下只贡献一个或两个响应。虽然来自不同个体的单侧响应可视为独立，但来自同一受试者的双侧响应可能存在相关性。已developed various statistical methods to account for this intra-subject correlation in the bilateral data, and in practice it is crucial to select an appropriate model for accurate inference. Tang et. al. (2012) discussed model selection issues using a variety of goodness-of-fit test statistics for correlated bilateral data for two groups, and Liu and Ma (2020) extended these methods to settings with $g\ge2$ groups. In this work, we investigate the goodness-of-fit statistics for the combined unilateral and bilateral data under different statistical models that address the intra-subject correlation, including the Clayton copula model, in addition to those considered in prior studies. Simulation results indicate that the performance of the goodness-of-fit tests is model-dependent, especially when the sample size is small and/or the intra-subject correlation is high, which is consistent with the findings by Liu and Ma (2020) for purely bilateral data. Applications to real data from otolaryngologic and ophthalmologic studies are included.