Pemodelan Regresi Zero Inflated Negative Binomial pada Data yang Mengalami Overdispersi

Abstract

Poisson regression is a nonlinear regression model with the response variables in the form of discrete data and Poisson distribution. Data analysis using Poisson regression must meet assumptions such as the variance value and the average value of the response variables have the same value. However, in its application, overdispersion often occurs, namely the variance value is greater than the average value. Overdispersion in Poisson regression can occur because of the number of zero observations on the response variable. Data with zero excess and overdispersion are more suitable for using ZINB regression. The ZINB regression model is a model formed from the mixed distribution of the Poisson gamma. The ZINB regression model parameters were estimated using the MLE method with the EM algorithm. This study was applied to data on the number of neonatal deaths in Makassar City in 2018. The results of testing the ZINB regression model parameters showed that the predictor variable that had a partially significant effect was the number of newborns with low birth weight.