Proposed method utilizes fixed effects and Bayesian models to analyze under-five mortality factors, suggesting improved data transparency.
Introduction Under-five mortality remains a significant public health challenge in East Africa, exacerbated by socioeconomic, environmental , and health systems inequities. This paper aims to provide a transparent and replicable methodology for studying the determinants of child mortality. Method A pragmatic and deductive research approach was followed, utilizing the research onion model. This model-based framework combines fixed effects models, additive regression, Cox models, Bayesian meta-analysis, and time series analysis, fitted to panel data with surveys from the DHS and the World Bank. Results Due to the methodological nature of this research, no empirical results are reported. However, the article provides processes for variable selection, data harmonization, model justification, and validation that should be carried out in further empirical research. Discussion The proposed method encourages transparency, reproducibility, and generalizability across data structures. It seeks to reinforce evidence-based child survival policy-making, strengthening the methodological quality of international health comparisons. Conclusions Cross-sectional and longitudinal under-five mortality studies have been conducted due to the use of structured methodology, and they inform future research and intervention strategies toward the attainment of SDG 3.2 in East Africa.
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Dlamini et al. (2025) studied this question.
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