Estimating and displaying population attributable fractions using the R package: graphPAF
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Updated: Jun 21, 2025

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Published on: December 7, 2021
John Ferguson1, Maurice O'Connell2
1Biostatistics Unit, HRB Clinical Research Facility Galway, University of Galway, Galway City, Ireland. john.ferguson@universityofgalway.ie.
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.
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