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A sensitivity analysis of two multivariate response models
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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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English
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Computational statistics and data analysis. - Amsterdam |
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| Publication |
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Amsterdam : 1994
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0167-9473
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17:4(1994), p. 363-391
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| ISI |
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A1994NF78700002
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