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Approximately Optimal One-Parameter Boundaries for Group Sequential Trials
Abstract
We present a class of group sequential tests, indexed by a single parameter, that yields approximately optimal results. We also provide tables of key values to help in the design of group sequential tests that meet selected specifications.
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“The interim analysis on patients who achieved stable remission did not show superiority of esketamine and antidepressant over antidepressant and placebo (at a 2-sided significance level of .0097,log-rank test); therefore, the study continued, and the number of relapses in patients who achieved stable remission was reestimated to 59 relapses in total with an adjusted significance level of .046(2-s”
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Metadata
- Authors
- Wang, S. K., & Tsiatis, A. A.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1987-03
- Volume
- 43
- Issue
- 1
- Pages
- 193
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W2090824711
- Cited by
- 341
- References
- 4
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 10 · 2023: 8 · 2022: 7 · 2021: 11 · 2020: 8 · 2019: 10 · 2018: 13 · 2017: 5 · 2016: 13 · 2015: 9 · 2014: 20 · 2013: 8 · 2012: 25
- FWCI
- 4.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biometrics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (CA23415, CA-35446)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- group sequential tests, approximate optimality, clinical trial design, stopping boundaries
- MeSH terms
- Clinical Trials as Topic, Humans, Statistics as Topic
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