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Title
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A sensitivity analysis of two multivariate response models
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Author
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Abstract
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| 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. |
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Language
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English
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Source (journal)
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Computational statistics and data analysis / International Association for Statistical Computing. - Amsterdam, 1983, currens
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Publication
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Amsterdam
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North-Holland
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1994
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ISSN
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0167-9473
[print]
1872-7352
[online]
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DOI
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10.1016/0167-9473(94)90018-3
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Volume/pages
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17
:4
(1994)
, p. 363-391
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ISI
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A1994NF78700002
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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