Random effects regression models for count data with excess zeros in caries research

D. Todem, Y. Zhang, A. Ismail and W. Sohn

Journal of Applied Statistics, 2010, vol. 37, issue 10, 1661-1679

Abstract: We extend the family of Poisson and negative binomial models to derive the joint distribution of clustered count outcomes with extra zeros. Two random effects models are formulated. The first model assumes a shared random effects term between the conditional probability of perfect zeros and the conditional mean of the imperfect state. The second formulation relaxes the shared random effects assumption by relating the conditional probability of perfect zeros and the conditional mean of the imperfect state to two different but correlated random effects variables. Under the conditional independence and the missing data at random assumption, a direct optimization of the marginal likelihood and an EM algorithm are proposed to fit the proposed models. Our proposed models are fitted to dental caries counts of children under the age of six in the city of Detroit.

Keywords: adaptive Gaussian quadrature; dental caries scores; clustered data; factor loadings; inflated zeros; negative binomial/Poisson distribution; random effects (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (1)

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DOI: 10.1080/02664760903127605

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