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Calibrate thresholds

calibrate_thresholds()
Calibrate according to posterior probability threshold and predictive probability threshold with interim futility monitoring
calibrate_posterior_threshold()
Calibrate the posterior probability threshold

Identify the optimal design

optimize_design()
Function to setup usage of optimize_design.calibrate_thresholds
optimize_design(<calibrate_thresholds>)
Custom optimization method for calibrate_thresholds objects

Calculate decision rules

calc_decision_rules()
Calculate a decision rule table for interim monitoring of a pre-specified design

Plotting and printing

plot(<calibrate_thresholds>)
Plot method for calibrate_thresholds objects
print(<calibrate_thresholds>)
Print method for calibrate_thresholds objects
plot(<calc_decision_rules>)
Plot method for calc_decision_rules objects

Data files

one_sample_cal_tbl
Output from a one-sample call to calibrate_thresholds
one_sample_decision_tbl
Output from a one-sample call to calc_decision_rules
two_sample_cal_tbl
Output from a two-sample call to calibrate_thresholds
two_sample_decision_tbl
Output from a two-sample call to calc_decision_rules

Support functions

calc_posterior()
Calculate a single posterior probability
calc_predictive()
Calculate a single posterior predictive probability
calc_next()
Calculate response probability for the next patient
eval_thresh()
Evaluate a single dataset for a single pp_threshold and ppp_threshold combination
sim_dat1()
Simulate a single dataset based on the response probability(ies), the total sample size(s), and the interim look schedule(s)
sim_single_trial()
Simulate a single trial with posterior probability monitoring