Hi, I'm using SAS Enterprise Guide to fit a model that aims to predict an ordinal variable ranging from 0 to 10, representing a rating. As predictors, I'm using binary, categorical, and continuous variables. I've tried both a simple regression model and also a logistic regression model using glogit, probit, and clogit as link functions. For the regression model, I obtained a reasonably good fit with an R-squared around 87%. However, when I look at the predicted values, they always range between 7.3 and 8.5 for all levels of the target variable. I assume that the tails of my response are not being properly captured even with the high R-squared. As for the logistic model, I have a higher misclassification rate even in the training data. I also tried balancing my sample to better capture the pattern between levels, but I encountered the same problem in both approaches (linear regression and logistic regression). Do you have any suggestions on which types of modeling I should use and how I can improve, i.e., obtain more accurate scores? Thank you.
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