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Testing Equivalence Simultaneously for Location and Dispersion of two Normally Distributed Populations

✍ Scribed by Peter Bauer; Michael M. Bauer


Publisher
John Wiley and Sons
Year
1994
Tongue
English
Weight
981 KB
Volume
36
Category
Article
ISSN
0323-3847

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✦ Synopsis


Abstract

In clinical trials with an active control usually therapeutical equivalence of a new treatment is investigated by looking at a location parameter of the distributions of the primary efficacy variable. But even if the location parameters are close to each other existing differences in variability may be connected with different risks for under or over treatment in an individual patient.

Assuming normally distributed responses a multiple test procedure applying two shifted one‐sided t‐tests for the mean and accordingly two one‐sided F‐tests for the variances is proposed. Equivalence in location and variability is established if all four tests lead to a rejection at the (one‐sided) level α. A conservative procedure “correcting” the t‐tests for heteroscedasticity is derived. The choice of a design in terms of the global level α, the global power, the relevant deviations in the population means and variances, as well as the sample size is outlined. Numerical calculations of the actual level and power for the proposed designs show, that for balanced sample sizes the classical uncorrected one‐sided t‐tests can be used safely without exaggerating the global type I error probability.

Finally an example is given.


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Sample size determination for proving eq
✍ Dieter Hauschke; Meinhard Kieser; Edgar Diletti; Martin Burke 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 137 KB 👁 2 views

Equivalence trials aim to demonstrate that two treatments do not differ by more than a prespecified clinically irrelevant amount. We consider the problem when equivalence is defined in terms of the ratio of population means and the original (untransformed) data are normally distributed. Application