Causal inference with multistate models—estimands and estimators of the population attributable fraction

Maja von Cube, Martin Schumacher and Martin Wolkewitz

Journal of the Royal Statistical Society Series A, 2020, vol. 183, issue 4, 1479-1500

Abstract: 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.

Date: 2020
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https://doi.org/10.1111/rssa.12486

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Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:183:y:2020:i:4:p:1479-1500

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