In this paper we provide a Random-Utility based derivation of the Dirichlet-Multinomial regression and posit 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 show how it relates with count models. Finally, we use a data set on patient choice of hospitals to illustrate an application of the Dirichlet-Multinomial regression.
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- Heckman, James J & Willis, Robert J, 1977.
"A Beta-logistic Model for the Analysis of Sequential Labor Force Participation by Married Women,"
Journal of Political Economy,
University of Chicago Press, vol. 85(1), pages 27-58, February.
- James J. Heckman & Robert J. Willis, 1975. "A Beta-Logistic Model for the Analysis of Sequential Labor Force Participation by Married Women," NBER Working Papers 0112, National Bureau of Economic Research, Inc.
- J. Shonkwiler & Nick Hanley, 2003. "A New Approach to Random Utility Modeling using the Dirichlet Multinomial Distribution," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 26(3), pages 401-416, November.
- Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984.
"Econometric Models for Count Data with an Application to the Patents-R&D Relationship,"
Econometric Society, vol. 52(4), pages 909-938, July.
- Jerry A. Hausman & Bronwyn H. Hall & Zvi Griliches, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," NBER Technical Working Papers 0017, National Bureau of Economic Research, Inc.
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