The goal of goldilocks is to implement the Goldilocks Bayesian
adaptive design proposed by Broglio et al. (2014) for time-to-event
endpoint trials, both one- and two-arm, with an underlying piecewise
exponential hazard model. The method can be used for a confirmatory trial
to select a trial's sample size based on accumulating data. During accrual,
frequent sample size selection analyses are made and predictive
probabilities are used to determine whether the current sample size is
sufficient or whether continuing accrual would be futile. The algorithm
explicitly accounts for complete follow-up of all patients before the
primary analysis is conducted. Broglio et al. (2014) refer to this as a
Goldilocks trial design, as it is constantly asking the question, <U+201C>Is the
sample size too big, too small, or just right?<U+201D>
Broglio KR, Connor JT, Berry SM. Not too big, not too small: a Goldilocks approach to sample size selection. Journal of Biopharmaceutical Statistics, 2014; 24(3): 685<U+2013>705.