In many medical studies, an ultimate failure event such as death is likely to be affected by the occurrence and timing of other intermediate clinical events. Both event times are subject to censoring by loss-to-follow-up but the nonterminal event may further be censored by the occurrence of the primary outcome, but not vice versa. To study the effect of an intervention on both events, the intermediate event may be viewed as a mediator, but conventional definition of direct and indirect effects is not applicable due to semi-competing risks data structure. We define three principal strata based on whether the potential intermediate event occurs before the potential failure event, which allow proper definition of direct and indirect effects in one stratum whereas total effects are defined for all strata. We discuss the identification conditions for stratum-specific effects, and proposed a semiparametric estimator based on a multivariate logistic stratum membership model and within-stratum proportional hazards models for the event times. By treating the unobserved stratum membership as a latent variable, we propose an EM algorithm for computation. We study the asymptotic properties of the estimators by the modern empirical process theory and examine the performance of the estimators in numerical studies.
翻译:在许多医学研究中,死亡等最终失败事件可能受到其他中间临床事件的发生和时机的影响。两种事件的时间都受到损失到跟踪的检查,但非终点事件可能受到主要结果的发生的进一步检查,而不是相反。为了研究干预这两个事件的影响,中间事件可被视为调解者,但直接和间接影响的常规定义不适用于半相互竞争的风险数据结构。我们根据潜在失败事件之前是否发生潜在中间事件确定了三个主要方面,从而可以适当界定某一层的直接和间接影响,而整个影响则是对所有层的界定。我们讨论对截断效应的确定条件,并根据多变后勤分层成员模式和事件时局内比例危害模型提出半参数估计。通过将未观测到的紧张成员作为潜在变量处理,我们提出计算EM算法。我们研究了现代实验理论和数字学研究中估量员的特征特性。