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Dirichlet-Multinomial Regression

  • Paulo Guimaraes

    (Medical University of South Carolina)

  • Richard Lindrooth

    (Medical University of South Carolina)

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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Paper provided by EconWPA in its series Econometrics with number 0509001.

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Length: 24 pages
Date of creation: 01 Sep 2005
Date of revision:
Handle: RePEc:wpa:wuwpem:0509001
Note: Type of Document - pdf; pages: 24
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  1. 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.
  2. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-38, July.
  3. J. Shonkwiler & Nick Hanley, 2003. "A New Approach to Random Utility Modeling using the Dirichlet Multinomial Distribution," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 26(3), pages 401-416, November.
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