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In Poisson regression analysis, there is an assumption that must be met, namely equidispersion (the variance value of the response variable is the same as the mean). In reality, conditions like this very rarely occur because overdispersion usually occurs (the variance value of the response variable is greater than the mean). One way to overcome this problem is to use the Negative Binomial regression method. The aim of this article is to obtain the best modeling results in Negative Binomial regression analysis to overcome overdispersion in cases of infant mortality in West Sumatra Province and West Java Province. The model obtained using Negative Binomial regression produces an AIC value in West Sumatra province of 192.65 which is smaller than the AIC value in West Java Province it was 283.47. Based on the Negative Binomial regression model equation obtained in West Sumatra Province, it can be explained that the number of health centers (X3) has a significant influence on the infant mortality rate and in West Java Province it can be explained that the number of medical personnel (X1) has a significant influence on the infant mortality rate.
Afdhal et al. (Fri,) studied this question.