What is estimated in cluster randomized crossover trials with informative sizes? -- A survey of estimands and common estimators
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信息性规模下的整群随机交叉试验究竟估计什么：目标量与常用估计量综述
- 研究问题
- 当治疗效应随群组、时期或群组时期规模变化时，整群随机交叉试验中的不同平均治疗效应目标量如何分化，常用估计量对应哪个目标？
- 方法与思路
- 作者区分个体、群组、群组时期和时期平均效应，分析两时期连续结局设计中不同加权方式与估计方程、固定效应及混合模型的对应关系。
- 材料陈述的贡献
- 摘要称，信息性规模下嵌套可交换混合模型的所考察估计量均不对应有意义目标；独立估计方程及特定情形下的其他模型可保持一致。
- 阅读关注点
- 应核对四类目标量的权重定义、信息性规模的具体形式，以及各估计量一致性所需条件，并查看模拟和住院时长重分析的设计。
- 阅读边界
- 这是 arXiv 预印本，同行评审及期刊接收未核实。摘要结论限于两时期横截面连续结局设计，具体条件及向其他设计的推广未说明。
原文摘要
In the analysis of cluster randomized trials (CRTs), previous work has defined two meaningful estimands: the individual-average treatment effect (iATE) and cluster-average treatment effect (cATE) estimand, to address individual and cluster-level hypotheses. In multi-period CRT designs, such as the cluster randomized crossover (CRXO) trial, additional weighted average treatment effect estimands help fully reflect the longitudinal nature of these trial designs, namely the cluster-period-average treatment effect (cpATE) and period-average treatment effect (pATE). We define different forms of informative sizes, where the treatment effects vary according to cluster, period, and/or cluster-period sizes, which subsequently cause these estimands to differ in magnitude. Under such conditions, we demonstrate which of the unweighted, inverse cluster-period size weighted, inverse cluster size weighted, and inverse period size weighted: (i.) independence estimating equation, (ii.) fixed effects model, (iii.) exchangeable mixed effects model, and (iv.) nested exchangeable mixed effects model treatment effect estimators are consistent for the aforementioned estimands in 2-period cross-sectional CRXO designs with continuous outcomes. We report a simulation study and conclude with a reanalysis of a CRXO trial testing different treatments on hospital length of stay among patients receiving invasive mechanical ventilation. Notably, with informative sizes, the unweighted and weighted nested exchangeable mixed effects model estimators are not consistent for any meaningful estimand and can yield biased results. In contrast, the unweighted and weighted independence estimating equation, and under specific scenarios, the fixed effects model and exchangeable mixed effects model, can yield consistent and empirically unbiased estimators for meaningful estimands in 2-period CRXO trials.