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

Yusuf Ob, Bello T and Gureje O
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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

Biostatistics and Biometrics Open Access Journal, 2017, vol. 1, issue 4, 69-75

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.

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:1:y:2017:i:4:p:69-75

DOI: 10.19080/BBOAJ.2017.01.555566

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