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Zero Inflated Poisson and Zero Inflated Negative Binomial Models with Application to Number of Falls in the Elderly

Author

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  • Yusuf OB

    (Department of Epidemiology and Medical Statistics, University of Ibadan, Nigeria)

  • Bello T

    (Department of Epidemiology and Medical Statistics, University of Ibadan, Nigeria)

  • Gureje O

    (Department of Epidemiology and Medical Statistics, University of Ibadan, Nigeria)

Abstract

The presence of excess zeros and the problem of over-dispersion often occur with count data. Few methods have been developed to deal with extra zeros that occur in response count variables. Such methods include zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) regression models. This analysis determined the best fitting model when the response variable is a count variable: number of falls in the elderly.

Suggested Citation

  • Yusuf OB & Bello T & Gureje O, 2017. "Zero Inflated Poisson and Zero Inflated Negative Binomial Models with Application to Number of Falls in the Elderly," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 1(4), pages 69-75, May.
    • Handle: RePEc:adp:jbboaj:v:1:y:2017:i:4:p:69-75
    DOI: 10.19080/BBOAJ.2017.01.555566
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    References listed on IDEAS

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    1. Hinde, John & Demetrio, Clarice G. B., 1998. "Overdispersion: Models and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 27(2), pages 151-170, April.
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