# Bayesian Prediction of Event Times for Blinded Randomized Controlled Trials

## 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