In Senegal, power-distribution equipment systems play a critical role in ensuring reliable electricity supply to households and businesses. A Bayesian hierarchical model was developed using data from multiple power-distribution sites in Senegal. This model incorporates uncertainty through robust standard errors to estimate the cost-effectiveness of equipment systems across various conditions. The analysis revealed a significant variation (p < 0. 05) in the cost-effectiveness metrics, indicating that regional and infrastructure-specific factors influence system performance. This study demonstrates how Bayesian hierarchical modelling can be used to assess power-distribution equipment systems' efficiency across diverse settings in Senegal. Future research could explore additional variables impacting system performance and validate findings through practical applications. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Clark et al. (Fri,) studied this question.
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