Causal inference with multi-state models - estimands and estimators of the population-attributable fraction
| Autor: | von Cube, Maja, Schumacher, Martin, Wolkewitz, Martin |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | J R Stat Soc A Stat, 2019 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1111/rssa.12486 |
| Popis: | 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 proportion of preventable cases after an elimination of exposure. Originally, the PAF has been 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 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. Comment: A revised version of this manuscript has been submitted to a journal on March 8 2019 |
| Databáze: | arXiv |
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