Methodological Evaluation of Field Research Stations in Kenya Using Multilevel Regression Analysis to Measure Yield Improvement

Field research stations in Kenya have been established to evaluate agricultural yield improvement interventions. However, their effectiveness is not well understood due to methodological limitations. Multilevel regression analysis was employed to assess the impact of agricultural interventions at both household and community levels. The model is specified as: Yᵢⱼ = eta₀ + eta₁Xᵢⱼ + b₀ⱼ + b₁ⱼZⱼ + uᵢⱼ, where Y represents yield, X is an intervention variable, Z is a contextual factor at the community level, and b₀ⱼ and b₁ⱼ are random effects capturing variation within communities. A significant proportion (35%) of households showed improved yields after participating in interventions compared to baseline levels. Random effects models indicated that community-level factors were more influential than household-specific variables. The multilevel regression analysis revealed the importance of considering both individual and contextual influences for accurate yield improvement measurements. Future research should incorporate community-level data to enhance the accuracy of yield measurement and inform policy interventions.