Generalized Poisson Regression Type-II at Jambi City Health Office

Corry Sormin,Gusmanely Z,Nurhidayah Nurhidayah

doi:10.24036/eksakta/vol21-iss1/222

Corry Sormin, Gusmanely Z + Show 1 more

Open Access

https://doi.org/10.24036/eksakta/vol21-iss1/222

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Abstract

One statistical analysis is regression analysis. One regression that has the assumption of poisson distribution is poisson regression which has the assumption of poisson distribution. Neonatal deaths are still very rare, so the proper analysis is used, namely Generalized Poisson Regression. This regression method is specifically used for Poissson distributed data. The stages that will be carried out in this research are Poisson distribution test and equidispersion assumption, parameter estimation, model feasibility test and best model selection. Data from the Jambi City Health Office in 2018 showed that the Generalized Poisson Regression regression alleged had a variable number of first trimester visits, the number of pregnant women getting Tetanus Diptheria immunization, the estimated number of neonatal infants with complications, the number of infants receiving Hepatitis B immunization was less than twenty-four hours, the number of infants receiving BCG immunizations.

Highlights

Statistics is one of the disciplines of science whose application has become widespread among the people
One regression that has the assumption of poisson distribution is poisson regression which has the assumption of poisson distribution
Data from the Jambi City Health Office in 2018 showed that the Generalized Poisson Regression regression alleged had a variable number of first trimester visits

Summary

Introduction

Statistics is one of the disciplines of science whose application has become widespread among the people. The analysis used if the second assumption is not met, that is, if the mean is greater or smaller than the value of variance, it is often referred to as underdispersion or overdispersion, so analyzes such as Negative Binomial Regression and Generalized Poisson Regression can be used Both of these regression analyzes have response variables in the form of discrete variables. Often the data obtained has a variance of the response variable greater than the average value (overdispersion), so the assumption of equi-dispersion (the mean and variance of the response variable is equal) in the Poisson regression is not met This shows that to overcome the problem of Underdispersion the Generalized Poisson Regression method is used

Generalized Poisson Regression

Conclusion