All functions

calc_NB_moments()

Calculates the first two moments of the bivariate distribution of NB_model and NB_all

calc_mROC_stats()

Calculates the absolute surface between the empirical and expected ROCs

calibration_plot()

Title Create calibration plot based on observed and predicted outcomes.

dev_data

model development data

evpi_val()

EVPI (Expected Value of Perfect Information) for validation Takes a vector of mean and a 2X2 covariance matrix

gusto

Anonymized data from the gusto trial

mAUC()

Takes in a mROC object and calculates the area under the curve

mROC()

Calculates mROC from the vector of predicted risks Takes in a vector of probabilities and returns mROC values (True positives, False Positives in an object of class mROC)

mROC_analysis()

Main eROC analysis that plots ROC and eROC

mROC_inference()

Statistical inference for comparing empirical and expected ROCs. If CI=TRUE then also returns pointwise CIs

mu_max_trunc_bvn()

Calculates the expected value of the maximum of two random variables with zero-truncated bivariate normal distribution Takes a vector of mean and a 2X2 covariance matrix

odds_adjust()

Title Update a prediction model for a binary outcome by multiplying a fixed odd-ratio to the predicted odds.

pred_summary_stat()

Title Estimate mean and variance of prediction based on model calibration output.

val_data

model validation data