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graphPAF (version 2.0.1)

Estimating and Displaying Population Attributable Fractions

Description

Estimation and display of various types of population attributable fraction and impact fractions. As well as the usual calculations of attributable fractions and impact fractions, functions are provided for attributable fraction nomograms and fan plots, continuous exposures, for pathway specific population attributable fractions, and for joint, average and sequential population attributable fractions.

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Install

install.packages('graphPAF')

Monthly Downloads

48

Version

2.0.1

License

MIT + file LICENSE

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Repository

https://github.com/johnfergusonNUIG/graphPAF

Maintainer

John Ferguson

Last Published

February 13th, 2026

Functions in graphPAF (2.0.1)

plot_continuous

Plot hazard ratios, odds ratios or risk ratios comparing differing values of a continuous exposure to a reference level

predict_df_continuous

Internal: Create a data frame for predictions (when risk factor is continuous).

Plot impact fractions corresponding to risk-quantiles over several risk factors

impact_fraction

General calculations of impact fractions

plot.SAF_summary

Produce plots of sequential and average PAF

Implementation of Miettinen's formula for summary data

Implementation of Levin's formula for summary data

predict_df_discrete

Internal: Create a data frame for predictions (when risk factor is discrete).

Calculation of joint attributable fractions over several risk factors taking into account risk factor sequencing

plot.rf.data.frame

Create a fan_plot of a rf.data.frame object

Simulated case control dataset for 6856 stroke cases and 6856 stroke controls

Print out PAF_q for differing risk factors

print.SAF_summary

Print out a SAF_summary object

Return the vector of risk quantiles for a continuous risk factor.

Create a rf.data.frame object

Internal: Simulate from the post intervention distribution corresponding to eliminating a risk factor

Calculation of sequential PAF taking into account risk factor sequencing

Internal, pathway specific PAF when the mediator is discrete

Estimate pathway specific population attributable fractions

Simulated case control dataset for 5000 cases (individuals with chronic cough) and 5000 controls

Internal: Simulate a column from the post intervention distribution corresponding to eliminating a risk factor

PAF_calc_discrete

Calculation of attributable fractions using a categorized risk factor

PAF_calc_continuous

Calculation of attributable fractions with a continuous exposure

Automatic fitting of probability models in a pre-specified Bayesian network.

Internal: Calculation of an impact fraction using the Bruzzi approach

Internal: Calculation of an impact fraction using the direct approach

Calculation of average and sequential paf taking into account risk factor sequencing

Clean a dataset to make model fitting more efficient

graphPAF-package

Estimating and Displaying Population Attributable Fractions