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Estimating and displaying population attributable fractions using the R package: graphPAF.

Authors :
Ferguson, John
O'Connell, Maurice
Source :
European Journal of Epidemiology; Jul2024, Vol. 39 Issue 7, p715-742, 28p
Publication Year :
2024

Abstract

Here we introduce graphPAF, a comprehensive R package designed for estimation, inference and display of population attributable fractions (PAF) and impact fractions. In addition to allowing inference for standard population attributable fractions and impact fractions, graphPAF facilitates display of attributable fractions over multiple risk factors using fan-plots and nomograms, calculations of attributable fractions for continuous exposures, inference for attributable fractions appropriate for specific risk factor → mediator → outcome pathways (pathway-specific attributable fractions) and Bayesian network-based calculations and inference for joint, sequential and average population attributable fractions in multi-risk factor scenarios. This article can be used as both a guide to the theory of attributable fraction estimation and a tutorial regarding how to use graphPAF in practical examples. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
BAYESIAN analysis
PACKAGING design

Details

Language :
English
ISSN :
03932990
Volume :
39
Issue :
7
Database :
Complementary Index
Journal :
European Journal of Epidemiology
Publication Type :
Academic Journal
Accession number :
179235496
Full Text :
https://doi.org/10.1007/s10654-024-01129-1