Bayesian hierarchical models are increasingly used in environmental studies to assess adoption rates of water treatment facilities across different regions. A Bayesian hierarchical model was applied to analyse data from multiple districts, accounting for spatial heterogeneity and varying adoption rates among regions. Uncertainty quantification is provided through credible intervals. The analysis revealed that the adoption rate of water treatment facilities varied significantly across different administrative zones in Ghana, with a notable proportion exceeding 50% in some areas. The Bayesian hierarchical model effectively captured spatial and temporal variations in water facility adoption, providing nuanced insights into regional disparities. Future studies should consider integrating additional socio-economic factors to enhance the predictive power of the model. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Parker-Hunt et al. (Mon,) studied this question.
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