I am trying to fit a three level model: observations ("t") nested in subjects ("id"), subjects cross-classified into municipalities -people have moved over time in my study so I can't use a simple nested structure ("MuniID"). I'd like to compute empirical rather than model-based standard errors for my fixed effects, but when I specify the empirical option in PROC MIXED, I get a warning that I only have one effective subject. The dimensions table says I only have one effective subject, though the class level information is correct - I have 5 waves in 1,741 people in 195 towns. I'm confused about why my dataset is read by SAS as having only one effective subject and how I can get the empirical standard errors I need. Anyone have any thoughts? Any advice would be greatly appreciated! Code: proc mixed data = obese method = ml; class ID t MuniID RACE SEX; model BMI= edu inc age RACE SEX density time time*time pctpov fcrate/ solution; repeated t/type =un subject=ID; random intercept / subject=MuniID; run; Output Dimensions Covariance Parameters 16 Columns in X 22 Columns in Z 195 Subjects 1 Max Obs Per Subject 20232 Class Level Information Class Levels ID 1741 t 5 MuniID 195 RACE 5 SEX 2
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