Skip to main navigation Skip to search Skip to main content

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

Research output: Contribution to journalConference articlepeer-review

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.

Original languageEnglish
Article number012051
JournalJournal of Physics: Conference Series
Volume943
Issue number1
DOIs
Publication statusPublished - 5 Feb 2018
Event1st Ahmad Dahlan International Conference on Mathematics and Mathematics Education, AD-INTERCOMME 2017 - Daerah Istimewa Yogyakarta, Indonesia
Duration: 13 Oct 201714 Oct 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Fingerprint

Dive into the research topics of 'Modeling Tetanus Neonatorum case using the regression of negative binomial and zero-inflated negative binomial'. Together they form a unique fingerprint.

Cite this