Open AccessOn Zero inflated models with applications to maternal healthcare utilization
Author(s) -
Uduak E. Bassey,
Mary Akinyemi,
Kelechi F. Njoku
Publication year - 2022
Publication title -
international journal of mathematical sciences and optimization: theory and application
Language(s) - English
Resource type - Journals
ISSN - 2814-0230
DOI - 10.52968/28309288
Subject(s) - count data , negative binomial distribution , poisson distribution , zero (linguistics) , overdispersion , zero inflated model , limit (mathematics) , poisson regression , binomial (polynomial) , econometrics , mathematics , statistics , dispersion (optics) , computer science , medicine , population , physics , optics , philosophy , linguistics , mathematical analysis , environmental health
We consider the problem of modelling count data with excess zeros and over-dispersion which are commonly encountered in various disciplines that limit the use of traditional models for count outcomes. Our research work applies the Zero-inflated Poisson and Negative Binomial models in modelling Maternal Health Care (MHC) utilization in Nigeria, employing the Andersen’s behavioural model to examine the effect of predisposing, enabling, and need factors on MHC utilization. The performance of these models are compared to the traditional Poisson and negative binomial models. The Vuong test and AIC suggests that the Zero-inflated Negative Binomial model provided the most significant improvement over traditional models for count outcomes.