Quasi-experimental designs are increasingly used in water treatment systems research to evaluate cost-effectiveness without random assignment. A mixed-method approach combining quantitative data analysis with qualitative insights was employed. The study utilised a hierarchical linear regression model to estimate cost-effectiveness ratios (CERs). The hierarchical linear regression model revealed significant differences in CERs across different water treatment facility types, indicating the need for tailored interventions. The findings suggest that specific design features and operational conditions significantly impact the cost-effectiveness of water treatment systems in Ghana. Further research should focus on evaluating the long-term sustainability and community acceptance of these facilities. water treatment, quasi-experimental design, hierarchical linear regression, cost-effectiveness The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Gyamfi et al. (Thu,) studied this question.
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