Bayesian Prediction of Event Times for Blinded Randomized Controlled Trials

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Documentation for package ‘BayesPET’ version 0.1.0

• DESCRIPTION file.
• Package NEWS.

Help Pages

BayesPET-package	BayesPET: Bayesian Prediction of Event Times for Blinded Randomized Controlled Trials
BayesPET	BayesPET: Bayesian Prediction of Event Times for Blinded Randomized Controlled Trials
convert_median	Solve baseline survival parameters by matching the marginal median survival time
data_example	Example trial datasets for fitting Stan models and predicting event times
fit_censor	Fit a Weibull model for random censoring times
fit_enroll	Fit enrollment model
fit_event_blind	Fit a Weibull event-time model with unknown treatment assignments
fit_event_unblind	Fit a Weibull event-time model with known treatment assignments
fit_models	Fit enrollment, event-time, and censoring models to clinical trial data and return posterior draws model parameters
generate_data	Generate two-arm trial data with enrollment, event, and censoring processes, and return data formatted for event-time prediction.
get_oc	Generate operating characteristics for event prediction
plot.BayesPET_predtime	Plot method for BayesPET prediction objects
predict_eventtime	Predict the calendar time at which a target number of events is reached from interim analysis data
print.BayesPET_fit	Print method for BayesPET model fitting objects
print.BayesPET_predtime	Print method for BayesPET prediction objects
print.summary.BayesPET_oc	Summary method for BayesPET operating characteristics object
print.summary.BayesPET_predtime	Summary method for BayesPET prediction objects
summary.BayesPET_oc	Summary method for BayesPET operating characteristics object
summary.BayesPET_predtime	Summary method for BayesPET prediction objects