%0 Journal Article
%A Ghosh, Abhik
%A Martín Apaolaza, Nirian
%A Basu, Ayanendranath
%A Pardo Llorente, Leandro
%T A New Class of Robust Two-Sample Wald-Type Tests
%D 2018
%@ 1557-4679
%@ 2194-573X
%U https://hdl.handle.net/20.500.14352/105575
%X Parametric hypothesis testing associated with two independent samples arises frequently in several applications in biology, medical sciences, epidemiology, reliability and many more. In this paper, we propose robust Wald-type tests for testing such two sample problems using the minimum density power divergence estimators of the underlying parameters. In particular, we consider the simple two-sample hypothesis concerning the full parametric homogeneity as well as the general two-sample (composite) hypotheses involving some nuisance parameters. The asymptotic and theoretical robustness properties of the proposed Wald-type tests have been developed for both the simple and general composite hypotheses. Some particular cases of testing against one-sided alternatives are discussed with specific attention to testing the effectiveness of a treatment in clinical trials. Performances of the proposed tests have also been illustrated numerically through appropriate real data examples.
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