The International Journal of Biostatistics
Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.
2 Issues per year
IMPACT FACTOR 2017: 0.840
5-year IMPACT FACTOR: 1.000
CiteScore 2017: 0.97
SCImago Journal Rank (SJR) 2017: 1.150
Source Normalized Impact per Paper (SNIP) 2017: 1.022
Mathematical Citation Quotient (MCQ) 2016: 0.09
The two one-sided tests procedure is used to test the equivalence of two measurements taken under different conditions. For example, two formulations of a drug are said to be bioequivalent if the average blood levels of the drug over time (AUC) are similar for the two formulations. In some studies there may be more than one parameter to test, such as a drug's AUC and maximum concentration, Cmax, or AUCs from a parent drug and a metabolite. The power of testing two or more equivalence hypotheses simultaneously is less than the power to test any one hypothesis separately, and depends on the correlations of the measurements. This paper develops an exact mathematical formula for the power for two or more simultaneous comparisons for normally distributed variables when several comparisons are evaluated separately. The formula requires numerical integration with respect to the variance-covariance terms. These terms are distributed according to the Wishart distribution, and are integrated over a subset of positive-definite matrices defined by the equivalence criteria. An R program for the case of two comparisons is included.
Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.