The population attributable fraction (PAF) is a popular epidemiological measure for the burden of a harmful exposure within a population. It is often interpreted causally as the proportion of preventable cases after an elimination of exposure. Originally, the PAF was defined for cohort studies of fixed length with a baseline exposure or cross‐sectional studies. An extension of the definition to complex time‐to‐event data is not straightforward. We revise the proposed approaches in the literature and provide a clear concept of the PAF for these data situations. The conceptualization is achieved by a proper differentiation between estimands and estimators as well as causal effect measures and measures of association.

中文翻译：

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多状态模型的因果推论—人口归因分数的估计和估计

人群归因分数（PAF）是流行的流行病学衡量指标，用于衡量人群中有害暴露的负担。通常将其解释为消除暴露后可预防病例的比例。最初，PAF定义为固定时间队列研究，基线暴露或横断面研究。将定义扩展到复杂的事件数据并不容易。我们修改了文献中提出的方法，并针对这些数据情况提供了PAF的清晰概念。概念化是通过适当区分估计数和估计数以及因果效应量度和关联量度来实现的。