R: Evaluate Clinical Prediction Models by Net Monetary Benefit

# Evaluate Clinical Prediction Models by Net Monetary Benefit

## Documentation for package ‘predictNMB’ version 0.2.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

autoplot.predictNMBscreen | Create plots of from screened predictNMB simulations.
autoplot.predictNMBsim | Create plots of from predictNMB simulations.
ce_plot | Create a cost-effectiveness plot.
ce_plot.predictNMBsim | Create a cost-effectiveness plot.
do_nmb_sim | Do the predictNMB simulation, evaluating the net monetary benefit (NMB) of the simulated model.
evaluate_cutpoint_cost | Evaluates a cutpoint by returning the mean treatment cost per sample.
evaluate_cutpoint_nmb | Evaluates a cutpoint by returning the mean NMB per sample.
evaluate_cutpoint_qalys | Evaluates a cutpoint by returning the mean QALYs lost per sample.
get_inbuilt_cutpoint | Get a cutpoint using the methods inbuilt to predictNMB
get_inbuilt_cutpoint_methods | Get a vector of all the inbuilt cutpoint methods
get_nmb_sampler | Make a NMB sampler for use in 'do_nmb_sim()' or 'screen_simulation_inputs()'
get_sample | Samples data for a prediction model with a specified AUC and prevalence.
get_thresholds | Gets probability thresholds given predicted probabilities, outcomes and NMB.
print.predictNMBscreen | Print a summary of a predictNMBscreen object
print.predictNMBsim | Print a summary of a predictNMBsim object
screen_simulation_inputs | Screen many simulation inputs: a parent function to 'do_nmb_sim()'
summary.predictNMBscreen | Create table summaries of 'predictNMBscreen' objects.
summary.predictNMBsim | Create table summaries of 'predictNMBsim' objects.
theme_sim | Returns a 'ggplot2' theme that reduces clutter in an 'autoplot()' of a 'predictNMBsim' object.