The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Bioequivalence trials, intersection-union tests and equivalence confidence sets
Abstract
The bioequivalence problem is of practical importance because the approval of most generic drugs in the United States and the European Community (EC) requires the establishment of bioequivalence between the brand-name drug and the proposed generic version. The problem is theoretically interesting because it has been recognized as one for which the desired inference, instead of the usual significant difference, is practical equivalence. The concept of intersection-union tests will be shown to clarify, simplify and unify bioequivalence testing. A test more powerful than the one currently specified by the FDA and EC guidelines will be derived. The claim that the bioequivalence problem defined in terms of the ratio of parameters is more difficult than the problem defined in terms of the difference of parameters will be refuted. The misconception that size-$\alpha$ bioequivalence tests generally correspond to $100(1 - 2 \alpha)%$ confidence sets will be shown to lead to incorrect statistical practices, and should be abandoned. Techniques for constructing $100(1 - \alpha)%$ confidence sets that correspond to size-$\alpha$ bioequivalence tests will be described. Finally, multiparameter bioequivalence problems will be discussed.
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Cites
Fisher, R. A. (1936) · BMJ · doi:10.1136/bmj.1.3923.554-a · Cited by 4,980
Schuirmann, D. J. (1987) · Journal of Pharmacokinetics and Biopharmaceutics · doi:10.1007/bf01068419 · Cited by 2,696
Cited by
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Hothorn, T., Hornik, K., & Zeileis, A. (2006) · Journal of Computational and Graphical Statistics · doi:10.1198/106186006x133933 · Cited by 4,021
Lakens, D. (2017) · Social Psychological and Personality Science · doi:10.1177/1948550617697177 · Cited by 2,161
“The two one-sided tests are rejected if t U (cid:2) t ( df , a ) , and t L (cid:4) t ( df , a ) , where t ( a , df ) is the upper 100 a percentile of a t -distribution (Berger & Hsu, 1996).”
The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis
Hoenig, J. M., & Heisey, D. M. (2001) · The American Statistician · doi:10.1198/000313001300339897 · Cited by 2,046
Sample sizes for clinical trials with normal data.
Julious, S. A. (2004) · Statistics in Medicine · doi:10.1002/sim.1783 · Cited by 605
Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars
Mayo, D. G. (2018) · doi:10.1017/9781107286184 · Cited by 376
Metadata
- Authors
- Berger, R. L., & Hsu, J. C.
- Venue
- Statistical Science
- Publisher
- Institute of Mathematical Statistics
- Published
- 1996-11-01
- Volume
- 11
- Issue
- 4
- Pages
- 283-319
- ISSN
- 0883-4237 (ISSN-L)
- OpenAlex
- W2114584570
- Cited by
- 620
- References
- 2
- FWCI
- 7.13
- Type
- journal article
- Language
- en
- Open access
- closed
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- Berger, R. L., & Hsu, J. C. (1996). Bioequivalence trials, intersection-union tests and equivalence confidence sets. Statistical Science. https://doi.org/10.1214/ss/1032280304
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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