Stratified-adjusted versus unstratified assessment of sample size and power for analyses of proportions
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In RCTs, investigators could claim that treatment directly affects the outcome even across subgroups of the baseline factor due to randomization of the treatment, assuming adequate sample size, adherence to the study protocol, and no differential loss to follow-up.
“In RCTs, investigators could claim that treatment directly affects the outcome even across subgroups of the baseline factor due to randomization of the treatment (assuming also adequate sample size, adherence to the study protocol, and no differential loss to follow-up).33”
From Understanding of interaction (subgroup) analysis in clinical trials (2019) · cites this paper as [33]
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References 17 · Cited by 12
- Authors
- Lachin, J. M., & Bautista, O. M.
- Affiliations
- George Washington University (US)
- ORCID
- Lachin, John M.
- Venue
- Cancer Treatment and Research
- Publisher
- Springer US
- Published
- 1995
- Volume
- 75
- Pages
- 203-223
- ISSN
- 0927-3042 (ISSN-L)
- OpenAlex
- W2096517934
- Cited by
- 12
- References
- 17
- Citations by year
- 2022: 1 · 2021: 1 · 2019: 1 · 2015: 1
- FWCI
- 6.94
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Cancer treatment and research (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- sample size determination, statistical power, stratified analysis, chi-square test, covariate effects, 2x2 contingency tables
- MeSH terms
- Data Interpretation, Statistical, Humans
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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