R: Estimating and Displaying Population Attributable Fractions

# Estimating and Displaying Population Attributable Fractions

## Documentation for package ‘graphPAF’ version 2.0.1

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

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