Man pages for ppseq
Design Clinical Trials using Sequential Predictive Probability Monitoring

calc_decision_rulesCalculate a decision rule table for interim monitoring of a...
calc_nextCalculate response probability for the next patient
calc_posteriorCalculate a single posterior probability
calc_predictiveCalculate a single posterior predictive probability
calibrate_posterior_thresholdCalibrate the posterior probability threshold
calibrate_thresholdsCalibrate according to posterior probability threshold and...
eval_threshEvaluate a single dataset for a single pp_threshold and...
one_sample_cal_tblOutput from a one-sample call to 'calibrate_thresholds'
one_sample_decision_tblOutput from a one-sample call to 'calc_decision_rules'
optimize_designFunction to setup usage of...
optimize_design.calibrate_thresholdsCustom optimization method for 'calibrate_thresholds' objects
plot.calc_decision_rulesPlot method for 'calc_decision_rules' objects
plot.calibrate_thresholdsPlot method for 'calibrate_thresholds' objects
ppseq-packageppseq: Design Clinical Trials using Sequential Predictive...
print.calibrate_thresholdsPrint method for 'calibrate_thresholds' objects
sim_dat1Simulate a single dataset based on the response...
sim_single_trialSimulate a single trial with posterior probability monitoring
two_sample_cal_tblOutput from a two-sample call to 'calibrate_thresholds'
two_sample_decision_tblOutput from a two-sample call to 'calc_decision_rules'
ppseq documentation built on April 18, 2023, 1:08 a.m.