I'm a new user of SAS. My thesis uses Lasso for fit the Multinomial Logistic Regression using Lasso. I used R earlier and I reckon that Lasso uses a more symmetric approach rather that the traditional K-1 logit model. My response was categorical. I have 4 categories: NoSchool, School1, School2, and School 3. I intend to make NoSchool as the reference category. Thus, I'll get 3 logit models for the outcome. I'd analyzed the common MLE methods for my multinomial logistic regression earlier using SPSS and I got my model. I need my Lasso estimation to be exactly presented like the common one, with 3 logits. But, when I use R to show the coefficient, all response's coefficient showed up (including NoSchool). I understand that according to Friedman, Hastie and Tibshirani (2010) that a more symmetric approach is used. But, my models need to be interpreted in the way MLE common multinomial logistics in SPSS did. Is there any possibility that I can do that? I spoke recently to Prof. Trevor Hastie himself through email, explaining the same situation. He suggest me that to make the coefficient comparable to SAS, I'll have to substract the glmnet coefficients (probably the one that I got from R result) for the class for which coefficients are missing in SAS from the others; then they are comparable. Excuse me but I'm new in SAS, and I really need help. any help would be highly appreciated. Thank you.
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