APPLICATION OF BINOMIAL AND BETA-BINOMIAL REGRESSION MODELS ON INCIDENCE OF DIARRHEA AMONG CHILDREN AGED 6-59 MONTHS IN MIESSO DISTRICT, OROMIA, ETHIOPIA

Authors

  • Fuad Redi Abdella Department of Statistics, Oda Bultum University, Chiro, Ethiopia
  • Lelisa Shemsadin Department of Statistics, Oda Bultum University, Chiro, Ethiopia

DOI:

https://doi.org/10.48165/

Keywords:

Binomial regression, β-binomial regression, over dispersion, diarrhea, children, Miesso, Ethiopia

Abstract

In binomial regression analysis model dependent variable follows a  binomial distribution. β-binomial model is a regression model for  outcomes following the β-binomial probability distribution. The aim of  present study was to fit binomial regression and beta-binomial regression  models for incidence of diarrhea, a prominent cause of health disorders/  deaths in under-five year age children. The study was conducted in the  children aged 6-59 months in Miesso Wereda, Oromia, Ethiopia from June  to September 2017. The data used was obtained from a cross-sectional  study using well-structured questionnaires. The Predictors used for the  current study were child sex, household food security status, sources of  drinking water, and toilet ownership status. Binomial and β-binomial  models were fitted to identify the significant predictors. The over dispersion status of the data was tested and revealed that there was no  over-dispersion and the fitted models had similar Akaiki information  criteria and Bayesian information Criteria with similar results. The source  of water (pipe water) and having toilet facility significantly affected the  incidence of diarrhea among the studied group of children. The study  recommended that giving attention to environmental sanitation and  creating pure water facility shall reduce diarrhea incidence in children. 

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Published

2023-11-16

How to Cite

APPLICATION OF BINOMIAL AND BETA-BINOMIAL REGRESSION MODELS ON INCIDENCE OF DIARRHEA AMONG CHILDREN AGED 6-59 MONTHS IN MIESSO DISTRICT, OROMIA, ETHIOPIA . (2023). Applied Biological Research, 24(3), 345–353. https://doi.org/10.48165/