589 – New Methods of Modeling Count Data and Its Impact on the Future Analysis of Health Data
A Multivariate Negative Binomial Regression Model
Sponsor: Health Policy Statistics Section
Keywords: count data, correlated data, over-dispersion, estimation
Felix Famoye
Central Michigan University
A multivariate negative binomial regression model based on the multivariate negative binomial distribution is defined and studied. The regression model can be used to describe a count data with over-dispersion. The model allows for both positive and negative correlation between any pair of the response variables. The parameters of the regression model are estimated by using the maximum likelihood method. Some test statistics are discussed and a numerical data set is used to illustrate the applications of the multivariate count data regression model.