|Title||Hypothesis testing for two-stage designs with over or under enrollment.|
|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Zeng, Donglin, Fei Gao, Kuolung Hu, Catherine Jia, and Joseph G. Ibrahim|
|Date Published||2015 Jul 20|
|Keywords||Biostatistics, Clinical Trials, Phase II as Topic, Computer Simulation, Confidence Intervals, Humans, Models, Statistical, Neoplasms, Sample Size|
Simon's two-stage designs are widely used in cancer phase II clinical trials for assessing the efficacy of a new treatment. However in practice, the actual sample size for the second stage is often different from the planned sample size, and the original inference procedure is no longer valid. Previous work on this problem has certain limitations in computation. In this paper, we attempt to maximize the unconditional power while controlling for the type I error for the modified second stage sample size. A normal approximation is used for computing the power, and the numerical results show that the approximation is accurate even under small sample sizes. The corresponding confidence intervals for the response rate are constructed by inverting the hypothesis test, and they have reasonable coverage while preserving the type I error.
|Alternate Journal||Stat Med|
|Original Publication||Hypothesis testing for two-stage designs with over or under enrollment.|
|PubMed Central ID||PMC4636905|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R01 GM047845 / GM / NIGMS NIH HHS / United States
Hypothesis testing for two-stage designs with over or under enrollment.