Controlling for overdispersion in grouped conditional logit models: A computationally simple application of Dirichlet‐multinomial regression
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Abstract
Summary In this article, we provide a random utility‐based derivation of the Dirichlet‐multinomial regression and propose it as a convenient alternative for dealing with overdispersed multinomial data. We show that this model is a natural extension of McFadden's conditional logit for grouped data and discuss its relationship with count models. Finally, we use a data set on patient choice of hospitals to illustrate an application of the Dirichlet‐multinomial regression.
