BayesPET-package        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
summary.BayesPET_oc     Summary method for BayesPET operating
                        characteristics object
summary.BayesPET_predtime
                        Summary method for BayesPET prediction objects
