Adaptive Trial Designs for Survival and Binary Endpoints

Documentation for package ‘goldilocks’ version 1.0.0

enrollment	Simulate exact continuous-time enrollment
evaluate_interim	Evaluate an externally observed interim data cut
goldilocks	Goldilocks Bayesian adaptive trial designs
plot_enrollment	Plot an enrollment projection
plot_sim_decisions	Plot predictive-probability decision maps
plot_sim_ocs	Plot operating characteristics across simulation scenarios
plot_sim_stopping	Plot stopping outcomes from trial simulations
plot_trial_trace	Plot predictive probabilities and enrollment at interim looks
ppwe	Calculate endpoint event probabilities from piecewise hazards
print.goldilocks_calendar_summary	Print a calendar-time operating-characteristic summary
print.goldilocks_interim	Print an externally evaluated interim analysis
print.goldilocks_trial	Print a Goldilocks adaptive trial result
prop_to_haz	Derive piecewise-constant hazard rates from cumulative event probabilities
pwe_impute	Impute piecewise exponential time-to-event outcomes
pwe_sim	Simulate piecewise exponential time-to-event outcomes
randomization	Generate a block-randomized treatment sequence
sim_comp_data	Simulate complete trial data under piecewise-exponential event rates
sim_trials	Estimate operating characteristics by trial simulation
summarise_calendar_time	Summarize operating characteristics on the calendar-time scale
summarise_sims	Estimate operating characteristics from trial simulations
summarise_trial_trace	Summarize an interim decision path
survival_adapt	Simulate and analyze one Goldilocks adaptive trial