Estimating and Displaying Population Attributable Fractions

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Documentation for package ‘graphPAF’ version 2.0.0

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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
graphPAF Estimating and Displaying Population Attributable Fractions
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