Negative Binomial Regression in Underdispersion(Case Study: Neonatal Mortality in Jambi City)

Abstract

Neonatalis is birth before 28 days of a baby. Factors that are considered to affect neonatal mortality include the number of visits in the 1st and 3 rd trimester, the number of pregnant women receiving Tetanus Diptheria Immunization, the estimated number of neonatal infants with complications, the number of infants receiving Hepatitis B Immunization for less than 24 hours, the number of infants receiving BCG Immunization and number of 1 and 3 neonatal visits. Neonatal mortality is still very rare so that the right analysis is used, namely Negative Binomial Regression. This research aim to investigate negative binomial regression in underdipersion on neonatal mortality at Jambi City. These two regression methods are specifically used for Poisson distributed data because they are rare. The stages of the research that will be carried out are the Poisson distribution test and the equidispersion assumption, parameter estimation, model feasibility test, and selection of the best model. The results obtained that the best model without the variable number of 3rd-trimester visits or without the variable number of infants who received BCG immunization with AIC was 36.3.