I am getting the following notes using PROC REG in my output: Model is not full rank. Least-squares solutions for the parameters are not unique. Some statistics will be misleading. A reported DF of 0 or B means that the estimate is biased. The following parameters have been set to 0, since the variables are a linear combination of other variables as shown. other = Intercept - lung - heart - esrd female = Intercept - male other_race = Intercept - white_race - black_race - hisp_race The three groups of variables as part of the model are being used as flags, where one and only one of the variables can have a value of 1, and the others 0 (example:If Male is 1, Female is 0 and vice versa). Other variables listed in the model statement are non-binary. Code looks as follows: proc reg data=data alpha=.05; model age=risk_score living lung heart esrd other count_visits male female white_race black_race hisp_race other_race median_income pop_density pct_rental; plot predicted.*residual. / name=Graph1; quit; run; I am not a statistician, so I can't really explain to my client what is happening. Why is SAS setting the "other" values to 0? I am getting the same behavior (same MODEL) using PROC AUTOREG.
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