An analyst fits a logistic regression model to predict whether or not a client will default on a loan. One of
the predictors in the model is agent, and each agent serves 15-20 clients each. The model fails to
converge. The analyst prints the summarized data, showing the number of defaulted loans per agent. See
the partial output below:

What is the most likely reason that the model fails to converge?

• A.There is quasi-complete separation in the data.
• B.There are missing values in the data.
• C.There are too many observations in the data.
• D.There is collinearity among the predictors.

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Within PROC GLM, the interaction between the two categorical predictors, Income and Gender, was shown to be significant. An item store was saved from the GLM analysis.
Which statement from PROC PLM would test the significance of Gender within each level of Income and adjust for multiple tests?

• A.sliceby Income / adjust=tukey;
• B.slice Income*Gender / sliceby=Gender adjust=tukey;
• C.sliceby Gender / adjust=tukey;
• D.slice Income*Gender / sliceby=Income adjust=tukey;

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