In this study, using the "Multiple Indicators Cluster Survey 5" (MICS5) conducted by UNICEF in 2014, Republic of the Congo in the level of lower middleincome countries is taken to identify the risk factors affecting “child mortality under5” by using Poisson regression model, negative binomial (NB2) regression model, zeroinflated Poisson (ZIP) regression model and zeroinflated negative binomial (ZINB) regression model in the class of generalized linear models (GLMs). For this purpose, education (as attended to a school or not attended to a school), wealth index quintile (as poorest, second, middle, fourth and richest population wealth quintiles), area of residence (as rural or urban), mother's age (as 1519, 2024, 2529, 3034, 3539, 4044, 4549 years), breastfeeding status (as received breast milk or not received breast milk) and pregnancy method (as used any methods to avoid pregnancy or not) are taken as categorical independent variables as possible risk factors affecting “child mortality under5” in the Republic of the Congo. By using Rprogramme to statistically analyze the child mortality under5 data of this country, among the abovementioned regression models and zeroinflated regression models, “ZIP regression model” is found as the best model according to the information criteria (IC) as AIC, BIC, AICc and also loglikelihood values. Statistical interpretations and conclusions will be done according to this type of zeroinflated regression model for the Republic of the Congo “child mortality under5” data.
Acknowledgement: This study is a part of M.Sc. Thesis titled “An Application Based on ZeroInflated Poisson and Negative Binomial Regression Models” supervised by Assoc.Prof.Dr. Neslihan İYİT continuing at Selcuk University, Graduate School of Natural Sciences, Statistics Department.
Anahtar Kelimeler: Child Mortality Under5, Generalized Linear Model, Poisson Regression Model, Negative Binomial Regression Model, ZeroInflated Poisson Regression Model
