控制实验和观测研究中，集群观测是普遍存在的，并在多中心试验或纵向调查中自然出现。我们提出了一种新的模型，用于分析集群观测，其中边际分布由线性转换模型描述，相关性由联合多元正态分布描述。联合模型提供了边际分布的解析公式。由于转换模型的丰富性，这些技术适用于任何类型的响应变量，包括有界、偏斜、二进制、序数或生存反应。我们展示了如何在缺乏睡眠的基准数据集中放松反应时间的常见正常假设，并报告了臭名昭著的脚趾甲数据的边际比率。我们还讨论了两项旨在估计边际治疗效应的临床试验的分析。在第一项试验中，痛苦在有界的视觉模拟量表上被重复评估，并呈现了边际比例几率模型。第二个试验报告了直肠癌患者的无病生存情况，其中来自Weibull和Cox模型的边际危险率特别重要。实证评估比较了新方法与二元反应的一般估计方程和连续反应的条件混合效应模型的性能。一种实现方法可在 $\texttt{R}$ 系统的tram附加包中使用，并已在文献中的已建立的模型中进行了基准测试。©作者2022年。由牛津大学出版社出版。

Clustered observations are ubiquitous in controlled and observational studies and arise naturally in multicenter trials or longitudinal surveys. We present a novel model for the analysis of clustered observations where the marginal distributions are described by a linear transformation model and the correlations by a joint multivariate normal distribution. The joint model provides an analytic formula for the marginal distribution. Owing to the richness of transformation models, the techniques are applicable to any type of response variable, including bounded, skewed, binary, ordinal, or survival responses. We demonstrate how the common normal assumption for reaction times can be relaxed in the sleep deprivation benchmark data set and report marginal odds ratios for the notoriously difficult toe nail data. We furthermore discuss the analysis of two clinical trials aiming at the estimation of marginal treatment effects. In the first trial, pain was repeatedly assessed on a bounded visual analog scale and marginal proportional-odds models are presented. The second trial reported disease-free survival in rectal cancer patients, where the marginal hazard ratio from Weibull and Cox models is of special interest. An empirical evaluation compares the performance of the novel approach to general estimation equations for binary responses and to conditional mixed-effects models for continuous responses. An implementation is available in the tram add-on package to the $\texttt{R}$ system and was benchmarked against established models in the literature.© The Author 2022. Published by Oxford University Press.