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Compound Regression Models for Ordered Categorical Data
Authors:Gerhard Tutz
Abstract:A general class of sequential models for the analysis of ordered categorical variables is developed and discussed. The models apply if the ordinal response may be subdivided into two or more meaningful sets of response categories. The parametrization explicitly makes use of this subdivision. The models furnish a linear alternative to non-linear models which incorporate a scale parameter. They are shown to be special cases of multivariate generalized linear models. Applications are discussed with the use of several examples.
Keywords:Compound models  Generalized linear models  Ordered categories  Proportional odds  Sequential models  Logit models  Regression models  Ordinal response  Two-step models
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