Bivariate generalized Poisson regression model: applications on health care data

Hossein Zamani, Pouya Faroughi and Noriszura Ismail ()
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Hossein Zamani: Hormozgan University
Pouya Faroughi: Islamic Azad University
Noriszura Ismail: Universiti Kebangsaan Malaysia (UKM)

Empirical Economics, 2016, vol. 51, issue 4, No 15, 1607-1621

Abstract: Abstract This paper introduces several forms of bivariate generalized Poisson regression model (BGPR) which can be fitted to bivariate and correlated count data with covariates. The main advantage of these forms of BGPR is that they are nested and thus they allow likelihood ratio tests to be performed to choose the best model. The BGPR can be fitted not only to bivariate count data with positive, zero, or negative correlations, but also to under- or overdispersed bivariate count data with flexible form of mean–variance relationship. Applications of several forms of the BGPR are illustrated on two sets of count data: the Australian health survey data and the US National Medical Expenditure Survey data.

Keywords: Generalized Poisson; Bivariate; Correlation; Overdispersion; Underdispersion (search for similar items in EconPapers)
JEL-codes: C35 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s00181-015-1051-7

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