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Title: | A Sensitivity Analysis of two Multivariate Response Models | Authors: | LESAFFRE, Emmanuel VERBEKE, Geert MOLENBERGHS, Geert |
Issue Date: | 1994 | Source: | Computational Statistics and Data Analysis, 17(4), p. 363-391 | Abstract: | Using extensive Monte Carlo simulations, the sensitivity of two multivariate response models with respect to their underlying assumptions is investigated: the Multivariate Probit Model, already suggested in 1970 by Ashford and Sowden [4] and the Multivariate Global Cross Ratio Model, a generalization of Dale's model (see [7]). Both types of models are designed to regress a multivariate, ordered, categorical response vector on discrete and/or continuous measurements. This paper focuses on the behaviour of the maximum likelihood estimate of the association parameters mainly under misspecification of the marginal distributions. The investigation will be restricted to 2- and 3-dimensional response models. The use of the two models is illustrated on a medical and a biological data set. | Keywords: | association; generalized linear models; multivariate dale model; multivariate probit model; odds ratio; ordinal variables; polychoric correlation; tetrachoric correlation | Document URI: | http://hdl.handle.net/1942/312 | ISSN: | 0167-9473 | e-ISSN: | 1872-7352 | DOI: | 10.1016/0167-9473(94)90018-3 | ISI #: | A1994NF78700002 | Rights: | (C) 1994 - Elsevier Science B.V. All rights reserved | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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