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Analyzing Overdispersed Antenatal Care Count Data in Bangladesh: Mixed Poisson Regression with Individual-Level Random Effects

Authors

  • Zakir Hossain University of Dhaka
  • Maria University of Dhaka

Abstract

Poisson regression (PR) is commonly used as the base model for analyzing count data with the restrictive equidispersion property. However, overdispersed nature of count data is very common in health sciences. In such cases, PR produces misleading inferences and hence give incorrect interpretations of the results. Mixed Poisson regression with individual--level random effects (MPR_ILRE) is a further improvement for analyzing such data. We compare MPR_ILRE with PR, quasi-Poisson regression (Q_PR) and negative binomial regression (NBR) for modelling overdispersed antenatal care (ANC) count data extracted from the latest Bangladesh Demographic and Health Survey (BDHS) 2014. MPR_ILRE is found to be the best choice because of its minimum Akaike information criterion (AIC) value and the overdispersion exists in data has also been modelled very well. Study findings reveal that on average, women attended less than three ANC visits and only 6.5\% women received the World Health Organization (WHO) recommended eight or more ANC visits for the safe pregnancy and child birth. Administrative division, place of residence, birth order, exposure of media, education, wealth index and body mass index (BMI) have significant impact on adequate ANC attendance of women to reducing pregnancy complications, maternal and child deaths in Bangladesh.

Author Biography

Zakir Hossain, University of Dhaka

I have completed the second MSc in Statistics from University of Nottingham, UK and PhD (Statistics) from Queen Mary University of London, UK in 2017. I am currently working as Associate Professor at the Department of Statistics, University of Dhaka, Bangladesh. 

My ORCID id: http://orcid.org/0000-0003-4128-3097}{orcid.org/0000-0003-4128-3097 

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How to Cite

Hossain, Z., & Maria. Analyzing Overdispersed Antenatal Care Count Data in Bangladesh: Mixed Poisson Regression with Individual-Level Random Effects. Austrian Journal of Statistics, 50(4), 78–90. Retrieved from https://ajs.or.at/index.php/ajs/article/view/1163