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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI
Anggun Qur'ani
Mathematics Study Programme, Udayana University, Indonesia
Mathematics

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The Robust Negative Binomial Regression Model on Under-five Mortality due to Pneumonia in the Province of East Java Anggun Qur'ani; Chandra Sari Widyaningrum; Sa’adatur Rohimiyah
Jurnal Matematika, Statistika dan Komputasi Vol. 21 No. 1 (2024): SEPTEMBER 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v21i1.34512

Abstract

Robust Negative Binomial regression model (RNBR) is a modelling method to overcome a problem if there are outliers and overdispersion in the data. Outliers are data points that are significantly different from other data. Outliers have a significant effect on modelling to the resulting model. Furthermore, overdispersion is indicated by the presence of too large values of Pearson statistics. In this study, the RNBR model was used to determine the factors of the toddler immune variable at post neonatal age that significantly influenced the number of under-five deaths caused by pneumonia in East Java Province. Based on the modelling obtained, it shows that the RNBR model provides more robust results in handling outlier and overdispersion problems. This can be seen from the AIC value of the RNBR model is smaller than the AIC of the Poisson regression model. In addition, and which are measures of the influence of outliers on the model, decreased from 1 for the Poisson regression model to around 0.42 for the RNBR model.
Co-Authors Chandra Sari Widyaningrum Sa’adatur Rohimiyah