Using Complex Samples Logistic Regression to Assess Credit Risk

If you are a loan officer at a bank, you want to be able to identify characteristics that are indicative of people who are likely to default on loans and then use those characteristics to identify good and bad credit risks.

Suppose that a loan officer has collected past records of customers given loans at several different branches, according to a complex design. This information is contained in bankloan_cs.sav. See the topic Sample Files for more information. The officer wants to see if the probability with which a customer defaults is related to age, employment history, and amount of credit debt, incorporating the sampling design.

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