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Activity Number:
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383
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #303242 |
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Title:
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On the Bivariate Negative Binomial Regression Model
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Author(s):
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K. Felix Famoye*+
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Companies:
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Central Michigan University
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Address:
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Department of Mathematics, Mt. Pleasant, MI, 48859,
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Keywords:
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correlated count data ; over-dispersion ; goodness of fit ; estimation
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Abstract:
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The bivariate negative binomial models obtained through the method of trivariate reduction can be used to describe count data with positive correlation. In this paper, a new bivariate negative binomial regression model that allows any type of correlation is defined and studied. The marginal means of the bivariate model are functions of the explanatory variables. The parameters of the bivariate regression model are estimated by using the maximum likelihood method. Some test statistics including goodness of fit are discussed. One numerical data set is used to illustrate the techniques.
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