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graphPAF (version 2.0.0)

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

284

Version

2.0.0

License

MIT + file LICENSE

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Repository

https://github.com/johnfergusonNUIG/graphPAF

Maintainer

John Ferguson

Last Published

December 21st, 2023

Functions in graphPAF (2.0.0)

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

Estimating and Displaying Population Attributable Fractions

Print out PAF_q for differing risk factors

print.SAF_summary

Print out a SAF_summary object

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

PAF_calc_continuous

Calculation of attributable fractions with a continuous exposure

predict_df_continuous

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

predict_df_discrete

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

PAF_calc_discrete

Calculation of attributable fractions using a categorized risk factor

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

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

plot.SAF_summary

Produce plots of sequential and average PAF

Implementation of Levin's formula for summary data

Internal: Calculation of an impact fraction using the Bruzzi approach

Internal: Calculation of an impact fraction using the direct approach

impact_fraction

General calculations of impact fractions

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

Implementation of Miettinen's formula for summary data

Create a rf.data.frame object

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

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

Calculation of sequential PAF taking into account risk factor sequencing

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

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

Clean a dataset to make model fitting more efficient

plot.rf.data.frame

Create a fan_plot of a rf.data.frame object

plot_continuous

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

Estimate pathway specific population attributable fractions

Internal, pathway specific PAF when the mediator is discrete