Zero-Inflated Models for Count Data: An Application to Number of Antenatal Care Service Visits
نویسندگان
چکیده
Abstract The risk of maternal death in developing countries is projected to be one 61, while for developed it estimated 2800. Antenatal care a protective obstetric health system aimed at improving the outcome pregnant fetus by routine pregnancy monitoring. One most important functions antenatal offer information and services that can significantly improve women their infants. 6450 from Ethiopian Demographic Health Survey 2016 were used analyze determinants barriers number service visits among Ethiopia. data found have excess zeros (35%); thus several count models such as Poisson, Negative Binomial, Zero Inflated Binomial Hurdle regression modeled fitted. From exploratory analysis results showed those eligible women, was seen 2240 (34.7%) them did not visit during periods months. visualization using scatter plot depicts all variables selected modeling an influence on event visiting cervices each these had opposite slope non-zero events respective categories. To select model which best fits data, compared based Akaike criterion value simulation study. experiment revealed zero-inflated as; fitted better than classical Poisson Binomial. Each Voung test characterized high variability any other models. In this study, education, partner education level, age mothers, religion mothers wealth index are major predictors utilization. Through experiment, suggests (ZI) zero inflated therefore, parsimonious model.
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ژورنال
عنوان ژورنال: Annals of Data Science
سال: 2021
ISSN: ['2198-5804', '2198-5812']
DOI: https://doi.org/10.1007/s40745-021-00328-x