Abstract
This chapter looks at regression models where the response is categorical. Both nominal and ordinal cases are considered. These include the multinomial logit model for nominal responses; and for ordinal responses: the proportional and non-proportional-odds models, continuation and stopping ratio models, and the adjacent categories model. Some other topics includes the xij argument for allowing η j -specific covariates, the Poisson trick, marginal effects, and genetic models.
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Yee, T.W. (2015). Categorical Data Analysis. In: Vector Generalized Linear and Additive Models. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2818-7_14
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