Testing for and against a stochastic ordering between multivariate multinomial populations
AbstractTests for comparing a multivariate response on a control and on a treatment population are considered. It is assumed that each component of the response is a categorical variable with ordered categories. In some situations it may be believed a priori that the treatment has a nondecreasing effect on each component of the response, and in such cases a test of equality of the two populations with a stochastically ordered alternative is of interest. In other situations, the stochastic ordering assumption may be questioned and one would want to test it as a null hypothesis. The likelihood ratio tests, as well as some chi-square analogues, for both of these situations are studied in the one- and two-sample cases. In the latter testing situation, equality of the two populations is shown to be asymptotically least favorable within the stochastic ordering hypothesis. A numerical example is given to illustrate the use of these tests.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Multivariate Analysis.
Volume (Year): 38 (1991)
Issue (Month): 2 (August)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Agresti, Alan & Coull, Brent A., 1998. "Order-restricted inference for monotone trend alternatives in contingency tables," Computational Statistics & Data Analysis, Elsevier, vol. 28(2), pages 139-155, August.
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