R: Design Clinical Trials using Sequential Predictive Probability Monitoring

# Design Clinical Trials using Sequential Predictive Probability Monitoring

## Documentation for package ‘ppseq’ version 0.2.5

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

calc_decision_rules | Calculate a decision rule table for interim monitoring of a pre-specified design
calc_next | Calculate response probability for the next patient
calc_posterior | Calculate a single posterior probability
calc_predictive | Calculate a single posterior predictive probability
calibrate_posterior_threshold | Calibrate the posterior probability threshold
calibrate_thresholds | Calibrate according to posterior probability threshold and predictive probability threshold with interim futility monitoring
eval_thresh | Evaluate a single dataset for a single pp_threshold and ppp_threshold combination
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'
optimize_design.calibrate_thresholds | Custom optimization method for 'calibrate_thresholds' objects
plot.calc_decision_rules | Plot method for 'calc_decision_rules' objects
plot.calibrate_thresholds | Plot method for 'calibrate_thresholds' objects
print.calibrate_thresholds | Print method for 'calibrate_thresholds' objects
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
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'