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 out a SAF_summary object
Simulated case control dataset for 5000 cases (individuals with chronic cough) and 5000 controls
Calculation of attributable fractions with a continuous exposure
Internal: Create a data frame for predictions (when risk factor is continuous).
Internal: Create a data frame for predictions (when risk factor is 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
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
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
Create a fan_plot of a rf.data.frame object
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