Evaluate Clinical Prediction Models by Net Monetary Benefit

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Documentation for package ‘predictNMB’ version 0.2.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

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.