The family income was defined as the total income was gained by all the family member.

The ordinal logistic model will be used to analysis the data of family income because the dependent variable is ordinal variable with more than two categories. This model is appropriate to deal with the ordinal dependent variable which has more than two categories.

Two models (Proportional Odds Model and Partial Proportional Odds Model) logistic models are used from the logistic models to analysis ordinal dependent variable (family income). The data of family income and the factors affected it was collected by using questionnaire and we use the STATA 14.2 software to analysis these data and apply these models.

When we use the Proportional Odds Model we find that some of independent variables do not meet Proportional Odds assumption, therefore the Partial Proportional Odds Model is used. According to this model the results show that the important factors which affect the  family income are  (number of the employee member in the family, gender of the householder, age of householder,  kind of work of householder and the monthly costs of the entertainment that were spend from the family).

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