Two‐phase outcome‐dependent sampling (ODS) designs are useful when resource constraints prohibit expensive exposure ascertainment on all study subjects. One class of ODS designs for longitudinal binary data stratifies subjects into three strata according to those who experience the event at none, some, or all follow‐up times. For time‐varying covariate effects, exclusively selecting subjects with response variation can yield highly efficient estimates. However, if interest lies in the association of a time‐invariant covariate, or the joint associations of time‐varying and time‐invariant covariates with the outcome, then the optimal design is unknown. Therefore, we propose a class of two‐wave two‐phase ODS designs for longitudinal binary data. We split the second‐phase sample selection into two waves, between which an interim design evaluation analysis is conducted. The interim design evaluation analysis uses first‐wave data to conduct a simulation‐based search for the optimal second‐wave design that will improve the likelihood of study success. Although we focus on longitudinal binary response data, the proposed design is general and can be applied to other response distributions. We believe that the proposed designs can be useful in settings where (1) the expected second‐phase sample size is fixed and one must tailor stratum‐specific sampling probabilities to maximize estimation efficiency, or (2) relative sampling probabilities are fixed across sampling strata and one must tailor sample size to achieve a desired precision. We describe the class of designs, examine finite sampling operating characteristics, and apply the designs to an exemplar longitudinal cohort study, the Lung Health Study.

中文翻译：

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双波两相结果相关采样设计，适用于纵向二进制数据

当资源限制禁止对所有研究对象进行昂贵的暴露确定时，两阶段结果依赖抽样 (ODS) 设计很有用。一类用于纵向二进制数据的 ODS 设计根据那些在没有、某些或所有后续时间经历事件的人将受试者分为三个层次。对于时变协变量效应，仅选择具有响应变化的受试者可以产生高效的估计。然而，如果兴趣在于时不变协变量的关联，或者时变和时不变协变量与结果的联合关联，那么最优设计是未知的。因此，我们提出了一类用于纵向二进制数据的双波两相 ODS 设计。我们将第二阶段的样本选择分为两个波，之间进行中期设计评估分析。中期设计评估分析使用第一波数据进行基于模拟的搜索，以寻找最佳的第二波设计，这将提高研究成功的可能性。虽然我们专注于纵向二进制响应数据，但所提出的设计是通用的，可以应用于其他响应分布。我们认为，所提出的设计在以下情况下很有用：（1）预期的第二阶段样本量是固定的，并且必须调整特定于层的抽样概率以最大限度地提高估计效率，或（2）相对抽样概率在抽样层中是固定的并且必须调整样本大小以达到所需的精度。我们描述设计类别，检查有限抽样操作特性，