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February 22, 20260 citationsOpen Access

Multilevel Regression Analysis to Evaluate and Enhance Water Treatment Facility Yields in Uganda's Context

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KKKabugo KasoziMSMusoke Sserunkuma

Key Points

  • The research aims to analyze and enhance water treatment facility yields in Uganda using multilevel regression methods.
  • Applied multilevel regression model to data from multiple water treatment sites.
  • Considered individual facility-level and contextual-level variables.
  • Model checked for robustness using heteroskedasticity-consistent errors.
  • Significant correlations found between infrastructure investment and improved yields (β = 0.35, p < 0.01).
  • Community participation positively impacts water treatment efficiency.
  • Recommendations made for targeted interventions to improve facility yields.

Abstract

Uganda faces challenges in maintaining consistent water treatment facility yields, necessitating methodological improvements to enhance efficiency and reliability. A multilevel regression model was applied to analyse data from multiple water treatment sites across Uganda. The model accounts for both individual facility-level and contextual-level variables. The multilevel regression revealed significant correlations between infrastructure investment, community participation, and improved yields (β = 0. 35, p < 0. 01), suggesting a positive impact on system performance. This study underscores the importance of integrated approaches in improving water treatment facility efficiency and recommends targeted interventions based on identified factors. Investment priorities should focus on infrastructure upgrades and community engagement programmes to enhance yield improvements in Ugandan water treatment facilities. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.

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Cite This Study

Kasozi et al. (2000) studied this question.

synapsesocial.com/papers/699a9dc0482488d673cd3ccdhttps://doi.org/10.5281/zenodo.18715968
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