Modeling and hypothesis testing for the factors affecting infant's diarrhea using Generalized Poisson Regression

B. W. Otok*, C. B.G. Allo, Purhadi

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


Infants are weak individuals. Number of infants with Diarrhea is count data. Count data can be modeled using Poisson Regression. Poisson Regression has assumption that must be met. In the real case, overdispersion or underdispersion often occurs in data. This condition causes Poisson Regression cannot be used to model the data. Another alternative used to model the data with violation of assumption in Poisson Regression is Generalized Poisson Regression. This article will estimate the parameters of Generalized Poisson Regression using Generalized Poisson Regression. After getting the estimate parameters, parameters hypothesis testing simultaneously is done using Maximum Likelihood Ratio Test. There are three independent variables. They are percentage of infants who get exclusive breastfeeding, percentage of infants who get complete basic immunization, and percentage of households who have healthy living behavior. Significant parameter used to build the model. So, model for the factors affecting Diarrhea in infants in Pasuruan Regency is a model consisting complete basic immunization and healthy living behavior in the model.

Original languageEnglish
Article number012063
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 19 Dec 2019
Event6th International Conference on Research, Implementation, and Education of Mathematics and Science, ICRIEMS 2019 - Yogyakarta, Indonesia
Duration: 12 Jul 201913 Jul 2019


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