Dear Ruth I have exactly the same problem. My data has about 70 variables that are to used in the logistic regression as predictor variables (all norminal with multiple levels) and I started by running a Pearson's Chi-Square between each of them and the binary outcome. Then I picked only the significant ones for my logistic regression which again are still too many (27 of them). I have tried running the model using Proc Genmod but it is not converging as a result of too many predictors I suppose. I thought of using Proc Logistic but the problem is that Proc Logistic does not allow you to specify the reference category in the class statement and I want particular categories as references. The advice I got from a friend is that I should run Spearman Rank Correlation between the predictors and then drop one of two highly correlated variables. I think this approach is not that bad and I suggest you try it Best Kingsly
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