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. |