Package: graphPAF 2.0.1

John Ferguson

graphPAF: Estimating and Displaying Population Attributable Fractions

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.

Authors:John Ferguson [aut, cre]

graphPAF_2.0.1.tar.gz
graphPAF_2.0.1.zip(r-4.7)graphPAF_2.0.1.zip(r-4.6)graphPAF_2.0.1.zip(r-4.5)
graphPAF_2.0.1.tgz(r-4.6-any)graphPAF_2.0.1.tgz(r-4.5-any)
graphPAF_2.0.1.tar.gz(r-4.7-any)graphPAF_2.0.1.tar.gz(r-4.6-any)
graphPAF_2.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
graphPAF/json (API)

# Install 'graphPAF' in R:

install.packages('graphPAF', repos = c('https://johnfergusonnuig.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/johnfergusonnuig/graphpaf/issues

Datasets:

Hordaland_data - Simulated case control dataset for 5000 cases (individuals with chronic cough) and 5000 controls
stroke_reduced - Simulated case control dataset for 6856 stroke cases and 6856 stroke controls

On CRAN:

3.85 score 7 stars 9 scripts 259 downloads 21 exports 41 dependencies

Last updated from:b4453d8df1. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	166
source / vignettes	OK	159
linux-release-x86_64	OK	147
macos-release-arm64	OK	105
macos-oldrel-arm64	OK	117
windows-devel	OK	178
windows-release	OK	137
windows-oldrel	OK	112
wasm-release	OK	93

Exports:automatic_fit average_paf data_clean do_sim if_bruzzi if_direct impact_fraction joint_paf PAF_calc_continuous PAF_calc_discrete paf_levin paf_miettinen plot_continuous predict_df_continuous predict_df_discrete ps_paf pspaf_discrete rf_summary risk_quantiles seq_paf sim_outnode

Dependencies:boot cli cpp11 dplyr expm farver generics ggplot2 ggrepel glue gridExtra gtable gtools isoband labeling lattice lifecycle madness magrittr MASS Matrix matrixcalc pillar pkgconfig plyr R6 RColorBrewer Rcpp reshape2 rlang S7 scales stringi stringr survival tibble tidyselect utf8 vctrs viridisLite withr

graphPAF: An R package to estimate and display population attributable fractions

Rendered fromgraphPAF_vignette.pdf.asisusingR.rsp::asis

Last update: 2025-05-09
Started: 2023-02-07

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Automatic fitting of probability models in a pre-specified Bayesian network.	automatic_fit
Calculation of average and sequential paf taking into account risk factor sequencing	average_paf
Clean a dataset to make model fitting more efficient	data_clean
Internal: Simulate a column from the post intervention distribution corresponding to eliminating a risk factor	do_sim
Simulated case control dataset for 5000 cases (individuals with chronic cough) and 5000 controls	Hordaland_data
Internal: Calculation of an impact fraction using the Bruzzi approach	if_bruzzi
Internal: Calculation of an impact fraction using the direct approach	if_direct
General calculations of impact fractions	impact_fraction
Calculation of joint attributable fractions over several risk factors taking into account risk factor sequencing	joint_paf
Calculation of attributable fractions with a continuous exposure	PAF_calc_continuous
Calculation of attributable fractions using a categorized risk factor	PAF_calc_discrete
Implementation of Levin's formula for summary data	paf_levin
Implementation of Miettinen's formula for summary data	paf_miettinen
Plot hazard ratios, odds ratios or risk ratios comparing differing values of a continuous exposure to a reference level	plot_continuous
Plot impact fractions corresponding to risk-quantiles over several risk factors	plot.PAF_q
Create a fan_plot of a rf.data.frame object	plot.rf.data.frame
Produce plots of sequential and average PAF	plot.SAF_summary
Internal: Create a data frame for predictions (when risk factor is continuous).	predict_df_continuous
Internal: Create a data frame for predictions (when risk factor is discrete).	predict_df_discrete
Print out PAF_q for differing risk factors	print.PAF_q
Print out a SAF_summary object	print.SAF_summary
Estimate pathway specific population attributable fractions	ps_paf
Internal, pathway specific PAF when the mediator is discrete	pspaf_discrete
Create a rf.data.frame object	rf_summary
Return the vector of risk quantiles for a continuous risk factor.	risk_quantiles
Calculation of sequential PAF taking into account risk factor sequencing	seq_paf
Internal: Simulate from the post intervention distribution corresponding to eliminating a risk factor	sim_outnode
Simulated case control dataset for 6856 stroke cases and 6856 stroke controls	stroke_reduced