{ "background": "The expansion and modernisation of power-distribution networks in developing economies require robust, data-driven methodologies to evaluate the cost-effectiveness of competing equipment systems. Current approaches often lack the statistical rigour to account for hierarchical data structures inherent in regional infrastructure projects.", "purpose and objectives": "This study aims to methodologically evaluate the application of multilevel regression modelling for assessing the cost-effectiveness of power-distribution equipment systems, using the Rwandan context as a case study. The objective is to determine the model's suitability for isolating system-level performance from regional implementation variables.", "methodology": "A three-level hierarchical linear model was specified: $\\text{Cost}{ijk} = \\beta{0jk} + \\beta{1}\\text{Load}{ijk} + u{0k} + v{0jk} + e_{ijk}$, where $i$, $j$, and $k$ index installations, districts, and provinces, respectively. Data comprised technical performance metrics and lifecycle cost records from multiple recent grid projects. Model estimation used restricted maximum likelihood with robust standard errors.", "findings": "The multilevel model successfully partitioned variance, revealing that 34% of the variation in cost-effectiveness was attributable to provincial-level differences in implementation. A one-standard-deviation increase in system load diversity was associated with a 12.7% improvement in cost-effectiveness (95% CI: 9.1% to 16.3%).", "conclusion": "Multilevel regression provides a statistically sound framework for cost-effectiveness analysis in power distribution, effectively disentangling equipment performance from geographical and administrative confounding factors.", "recommendations": "Infrastructure planners should adopt hierarchical modelling techniques for future comparative evaluations of engineering systems. Regulatory bodies should mandate the collection of granular, hierarchically structured data to enable such analyses.", "key words": "cost-benefit analysis, hierarchical linear model, infrastructure economics, power distribution networks, statistical methodology", "contribution statement": "This paper provides the first formal methodological evaluation and application of mult