Dairy agripreneurs’ preference for production and animal health support services in Kenya—a choice experiment

Understanding uptake and interrelationship of climatic agricultural innovations in rural Zambia: Evaluating seasonal climate forecast use and weather shocks

“…There are several techniques for detecting multicollinearity in the data, such as a higher r-squared with fewer significant t-ratios, higher pairwise corrections among the observed covariates, and high Variance Inflation factor (VIF) values exceeding an absolute value of 10 (rule of thumb) (Gujarati, 2015;Gujarati, 2003). Following Okello (2021), this study used the variance inflation factor (VIF) on continuous covariates to measure multicollinearity and pairwise correlations on dummy and/or categorical variables. As indicated in Table 2, the VIF for each observed continuous variable was less than 10, suggesting that multicollinearity among the continuous variables was absent.…”