Modeling Tetanus Neonatorum case using the regression of negative binomial and zero-inflated negative binomial

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Luthfatul Amaliana, Umu Sa'Adah, Ni Wayan Surya Wardhani

2018 Journal of Physics: Conference Series Vol. 943 Issue 1 Conference paper Cited by 2 Quartile

Abstract

Tetanus Neonatorum is an infectious disease that can be prevented by immunization. The number of Tetanus Neonatorum cases in East Java Province is the highest in Indonesia until 2015. Tetanus Neonatorum data contain over dispersion and big enough proportion of zero-inflation. Negative Binomial (NB) regression is an alternative method when over dispersion happens in Poisson regression. However, the data containing over dispersion and zero-inflation are more appropriately analyzed by using Zero-Inflated Negative Binomial (ZINB) regression. The purpose of this study are: (1) to model Tetanus Neonatorum cases in East Java Province with 71.05 percent proportion of zero-inflation by using NB and ZINB regression, (2) to obtain the best model. The result of this study indicates that ZINB is better than NB regression with smaller AIC. © Published under licence by IOP Publishing Ltd.

Affiliations

Brawijaya University, Jl. Veteran, Malang, 65145, Indonesia