The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
A comparison of the Two One-Sided Tests Procedure and the Power Approach for assessing the equivalence of average bioavailability
Open accessAbstract
The statistical test of hypothesis of no difference between the average bioavailabilities of two drug formulations, usually supplemented by an assessment of what the power of the statistical test would have been if the true averages had been inequivalent, continues to be used in the statistical analysis of bioavailability/bioequivalence studies. In the present article, this Power Approach (which in practice usually consists of testing the hypothesis of no difference at level 0.05 and requiring an estimated power of 0.80) is compared to another statistical approach, the Two One-Sided Tests Procedure, which leads to the same conclusion as the approach proposed by Westlake based on the usual (shortest) 1-2 alpha confidence interval for the true average difference. It is found that for the specific choice of alpha = 0.05 as the nominal level of the one-sided tests, the two one-sided tests procedure has uniformly superior properties to the power approach in most cases. The only cases where the power approach has superior properties when the true averages are equivalent correspond to cases where the chance of concluding equivalence with the power approach when the true averages are not equivalent exceeds 0.05. With appropriate choice of the nominal level of significance of the one-sided tests, the two one-sided tests procedure always has uniformly superior properties to the power approach. The two one-sided tests procedure is compared to the procedure proposed by Hauck and Anderson.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The simplest and most widely used approach to test equivalence is the two one-sided test (TOST) procedure 2 .”
From Understanding Equivalence and Noninferiority Testing (2011) · cites this paper as [2]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“We adopt equivalence testing (TOST) (Schuirmann, 1987), under which the null hypothesis is that the disparity equals or exceeds the regulatory tolerance. A model passes only when the data provide affirmative evidence that the disparity is within tolerance.”
From Fairness Testing for Algorithmic Pricing (2026) · cites this paper as Schuirmann, 1987
The cited source says what the claim attributes to it.
In the citing paper
“Using TOST, equivalence is established at the α significance level if a (1-2α) × 100% confidence interval for the difference in efficacies (newcurrent) is contained within the interval (-δ, δ) (Fig. 1).”
From Understanding Equivalence and Noninferiority Testing (2011) · cites this paper as [2]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A new procedure for testing equivalence in comparative bioavailability and other clinical trials
Anderson, S., & Hauck, W. W. (1983) · Communication in Statistics- Theory and Methods · doi:10.1080/03610928308828634 · Cited by 247
Bioequivalence Testing -- A Need to Rethink
Kirkwood, T. B. L., & Westlake, W. J. (1981) · Biometrics · doi:10.2307/2530573 · Cited by 222
A new statistical procedure for testing equivalence in two-group comparative bioavailability trials
Hauck, W. W., & Anderson, S. (1984) · Journal of Pharmacokinetics and Biopharmaceutics · doi:10.1007/bf01063612 · Cited by 209
Comparison of Different Methods for Decision-Making in Bioequivalence Assessment
Mandallaz, D., & Mau, J. (1981) · Biometrics · doi:10.2307/2530412 · Cited by 138
An exact confidence interval from untransformed data for the ratio of two formulation means
Locke, C. S. (1984) · Journal of Pharmacokinetics and Biopharmaceutics · doi:10.1007/bf01059558 · Cited by 84
Current concepts in the pharmaceutical sciences: dosage form design and bioavailability
Swarbrick, J. (1973) · Lea & Febiger eBooks · Cited by 79
On testing for bioequivalence.
Rocke, D. M. (1984) · PubMed · Cited by 37
Rocke, D. M. (1984) · Biometrics · doi:10.2307/2530763 · Cited by 29
Cited by
Sorted by citations
Lakens, D. (2017) · Social Psychological and Personality Science · doi:10.1177/1948550617697177 · Cited by 2,161
“A very simple equivalence testing approach is the “two one-sided tests” (TOST) procedure (Schuirmann, 1987).”
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
Dimidjian, S., Hollon, S. D., Dobson, K. S., Schmaling, K. B., Kohlenberg, R. J., Addis, M. E., Gallop, R., McGlinchey, J. B., Markley, D. K., Gollan, J. K., et al. (2006) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.74.4.658 · Cited by 1,607
Kruschke, J. K., & Liddell, T. M. (2018) · Psychonomic Bulletin & Review · doi:10.3758/s13423-016-1221-4 · Cited by 1,288
15 Design and Analysis of Cross-Over Trials
Kenward, M. G., & Jones, B. C. (2007) · Handbook of statistics · doi:10.1016/s0169-7161(07)27015-4 · Cited by 873
Metadata
- Authors
- Schuirmann, D. J.
- Affiliations
- United States Food and Drug Administration (US)
- Corresponding author
- Schuirmann, Donald J.
- Venue
- Journal of Pharmacokinetics and Biopharmaceutics
- Published
- 1987-12
- Volume
- 15
- Issue
- 6
- Pages
- 657-680
- ISSN
- 0090-466X (ISSN-L)
- OpenAlex
- W2037698344
- Cited by
- 2,696
- References
- 8
- Citations by year
- 2026: 229 · 2025: 113 · 2024: 97 · 2023: 91 · 2022: 101 · 2021: 104 · 2020: 115 · 2019: 106 · 2018: 112 · 2017: 89 · 2016: 75 · 2015: 65 · 2014: 86 · 2013: 69 · 2012: 74
- FWCI
- 14.93
- Type
- journal article
- Language
- en
- Open access
- green
- zenodo.org
- Licence
- public-domain
- www.springer.com/tdm (tdm)
- Locations
- Journal of Pharmacokinetics and Biopharmaceutics (publishedVersion)
- PubMed (publishedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, public-domain)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Life Sciences › Immunology and Microbiology › Immunology › Biosimilars and Bioanalytical Methods
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Keywords
- bioequivalence, statistical power, bioequivalence testing, confidence intervals, type I error, drug formulation
- MeSH terms
- Biological Availability, Models, Biological, Pharmacokinetics, Statistics as Topic
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
