Design Clinical Trials using Sequential Predictive Probability Monitoring
Calculate a decision rule table for interim monitoring of a pre-specif...
Calculate response probability for the next patient
Calculate a single posterior probability
Calculate a single posterior predictive probability
Calibrate the posterior probability threshold
Calibrate according to posterior probability threshold and predictive ...
Evaluate a single dataset for a single pp_threshold and ppp_threshold ...
Custom optimization method for calibrate_thresholds objects
Function to setup usage of optimize_design.calibrate_thresholds
Plot method for calc_decision_rules objects
Plot method for calibrate_thresholds objects
ppseq: Design Clinical Trials using Sequential Predictive Probability ...
Print method for calibrate_thresholds objects
Simulate a single dataset based on the response probability(ies), the ...
Simulate a single trial with posterior probability monitoring
Functions are available to calibrate designs over a range of posterior and predictive thresholds, to plot the various design options, and to obtain the operating characteristics of optimal accuracy and optimal efficiency designs.
Useful links