Optimization of Overdispersion Modeling in Low Birth Weight Cases in Central Sulawesi Using Conway-Maxwell Poisson Regression

Abstract

Low birth weight (LBW) is a condition of a baby weighing less than 2,500 grams where gestational age is not taken into account and the baby's weight is measured within 24 hours after birth. The level of infant development also plays an important role in determining the mortality rate and incidence rate of disease in infants with LBW. This study aims to find models and factors that influence LBW using Conway Maxwell Poisson Regression (CMPR). CMPR is an extension method of Poisson regression that has the advantage of overcoming violations of the equidispersion assumption, where data can experience overdispersion or underdispersion