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June 2005 Optimal testing of equivalence hypotheses
Joseph P. Romano
Ann. Statist. 33(3): 1036-1047 (June 2005). DOI: 10.1214/009053605000000048


In this paper we consider the construction of optimal tests of equivalence hypotheses. Specifically, assume X1,…,Xn are i.i.d. with distribution Pθ, with θ∈ℝk. Let g(θ) be some real-valued parameter of interest. The null hypothesis asserts g(θ)∉(a,b) versus the alternative g(θ)∈(a,b). For example, such hypotheses occur in bioequivalence studies where one may wish to show two drugs, a brand name and a proposed generic version, have the same therapeutic effect. Little optimal theory is available for such testing problems, and it is the purpose of this paper to provide an asymptotic optimality theory. Thus, we provide asymptotic upper bounds for what is achievable, as well as asymptotically uniformly most powerful test constructions that attain the bounds. The asymptotic theory is based on Le Cam’s notion of asymptotically normal experiments. In order to approximate a general problem by a limiting normal problem, a UMP equivalence test is obtained for testing the mean of a multivariate normal mean.


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Joseph P. Romano. "Optimal testing of equivalence hypotheses." Ann. Statist. 33 (3) 1036 - 1047, June 2005.


Published: June 2005
First available in Project Euclid: 1 July 2005

zbMATH: 1072.62012
MathSciNet: MR2195627
Digital Object Identifier: 10.1214/009053605000000048

Primary: 62F03 , 62F05

Keywords: Asymptotically maximin , efficiency , equivalence tests , Hypothesis tests , large sample theory

Rights: Copyright © 2005 Institute of Mathematical Statistics


Vol.33 • No. 3 • June 2005
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