Field research stations in Kenya play a crucial role in agricultural development and productivity enhancement. However, their effectiveness is influenced by various factors such as environmental conditions, socioeconomic status of local communities, and resource management practices. A multilevel regression model will be employed to analyse data collected from multiple levels including individual projects, regional collaborations, and national policies. This approach allows for the examination of both direct effects and indirect effects across different scales. This theoretical framework provides a robust methodological basis for assessing the performance of agricultural research stations in Kenya, emphasising the importance of integrated risk management strategies. Policy makers should prioritise investment in insurance programmes and infrastructure improvements to mitigate risks faced by research stations. Researchers can use this model to guide future studies on station performance evaluation. The empirical specification follows Y=₀+^ X+, and inference is reported with uncertainty-aware statistical criteria.
Gitonga et al. (Fri,) studied this question.