Some optimal and non-optimal two-stage designs using an alpha-spending function.
While designing a group sequential clinical trial in the pharmaceutical industry setting, we often face a problem of determining the time for an interim analysis. For a two-stage trial we compute the sample sizes n and N per treatment group for the interim and final analyses, respectively, that minimize the average trial size for a specified overall power. We consider this optimization when we monitor the trial using a Lan-DeMets alpha-spending function. Two additional problems considered in this context are (i) finding the sample sizes that maximize the overall power for a specified average trial size, and (ii) finding the sample sizes that achieve specified powers at the interim and final analyses.
Patel
H I
HI
Berlex Laboratories, Inc., Wayne, NJ 07470, USA.
D000465:Algorithms; D003362:Cost-Benefit Analysis; D004341:Drug Evaluation / Q000379:methods*; D006801:Humans; D012107:Research Design; D018401:Sample Size