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Sample Size Calculations in Clinical Research
Abstract
Focusing on an integral part of pharmaceutical development, Sample Size Calculations in Clinical Research, Second Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. It provides sample size formulas and procedures for testing equality, noninferiority/supe
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“In order to detect a 5% effect with p < 0.05 and β < 0.20, we estimate that such an experiment would require 66 days [10].”
From An Efficient Bandit Algorithm for Realtime Multivariate Optimization (2017) · cites this paper as [10]
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“Considering the primary clinical outcome of this trial (Depression Anxiety Stress Scale – 21 items), in order to achieve 80% power and expecting an approximate 25% dropout rate, a total of N = 92 participants were needed.”
From Inflammatory markers changes following acceptance-based behavioral psychotherapy in generalized anxiety disorder patients: Evidence from a randomized controlled trial (2024) · cites this paper as Chow et al., 2007
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Metadata
- Authors
- Chow, S.-C., Wang, H., & Shao, J.
- Venue
- Chapman & Hall/CRC eBooks
- Publisher
- Chapman and Hall/CRC
- Published
- 2007-08-22
- OpenAlex
- W4210615620
- Cited by
- 562
- References
- 0
- Citations by year
- 2026: 16 · 2025: 72 · 2024: 57 · 2023: 45 · 2022: 54 · 2021: 56 · 2020: 43 · 2019: 41 · 2018: 41 · 2017: 41 · 2016: 23 · 2015: 28 · 2014: 14 · 2013: 6 · 2012: 8
- FWCI
- 0.94
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Chapman & Hall/CRC eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Keywords
- sample size determination, clinical trials, drug development, non-inferiority testing, superiority testing, equivalence testing, statistical power
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