Comparative Performance of Classical and Bayesian Hierarchical Logistic Regression Models in Identifying Childhood Immunization Determinants in Nigeria
Akintunde Mutairu Oyewale *
Department of Statistics, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria.
Akintunde, Mubarak Ayodeji
Department of Nursing Science, Lead City University, Ibadan, Oyo State, Nigeria.
Popoola Kazeem Olanrewaju
Bursary Department, Federal University of Agriculture and Technology, Okeho, Oyo State, Nigeria.
Aje Oluranti Grace
Department of Statistics, Federal Polytechnic, Ede, Osun State, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Background: Complete childhood immunisation in Nigeria remains uneven across maternal, household, and healthcare contexts. This study identified determinants of complete childhood immunisation and compared classical and Bayesian hierarchical logistic regression models using the 2023–24 Nigeria Demographic and Health Survey.
Methods: Weighted descriptive statistics, survey-adjusted chi-square tests, survey-weighted logistic regression, multilevel modelling, and model-adequacy assessments were applied to children aged 12–23 months with complete study information.
Results: Overall, 58.0% of children were fully immunised, 32.0% were partially immunised, and 10.0% were unvaccinated. Maternal age, secondary and higher education, urban residence, household wealth, at least four antenatal care visits, and health-facility delivery were positively associated with complete immunisation. Four or more antenatal care visits showed the largest adjusted association (adjusted odds ratio = 2.04; 95% confidence interval: 1.79–2.34). The multilevel model indicated meaningful community-level variation, with an intraclass correlation coefficient of 0.126. Classical and Bayesian estimates were substantively similar; however, the Bayesian model showed slightly better discrimination, calibration, and predictive accuracy, with a higher area under the receiver operating characteristic curve and a lower Brier score.
Conclusion: Childhood immunisation in Nigeria is associated with maternal education, household resources, place of residence, and engagement with maternal healthcare services. Bayesian hierarchical modelling provides a useful framework for accounting for clustered survey data and quantifying uncertainty while supporting the identification of underserved populations.
Keywords: Childhood immunisation, maternal characteristics, Bayesian logistic regression, survey-weighted logistic regression, multilevel modelling, vaccination coverage