When working with smaller data sets (N<200), which method is preferred to perform honest assessment?
While building a predictive model, median imputations are performed while preparing the training data.
How should the imputations be addressed in the validation data?
Given the following output from the LOGISTIC procedure:
Which variables, among those that are statistically significant at an alpha of 0.05, have the greatest and least relative importance on the fitted model?
Which SAS program will correctly use backward elimination selection criterion within the REG procedure?