Additionally, the data highlighted that the likelihood for a HH to be either in the middle or in the highest categories of agricultural income rises when that household resides in a rural area.
The results also reiterated the fact that HH size has a significant influence on agricultural income of the households, since HHs with large size were more likely to be found in the lower category of agricultural income. The findings from this study revealed that households (HHs) owning at least one cow have more chances of being either in the middle or in the highest categories of agricultural income.
The Fisher test was used to analyze the goodness of fit of the model and hence it indicated that the model was statistically significant as a whole, meaning that the observed data perfectly corresponded to the fitted model. The discussed household agricultural income in this study were mainly generated from the sales of crops, processed products, livestock and livestock products, auto-consumption, rent of land and agricultural equipments. In analysis the dependent variable was classified into 3 groups namely: Low, Medium and High agricultural income. Basing on the nature of the variables in this study, an ordered logistic regression model (OLR) was used to statistically measure the relationship between an ordinal dependent variable (Agricultural income) and a set of independent variables. Abstract: The purpose of this research was mainly to measure the level of association between various differentials and household agricultural income in Rwanda.