Moved from Programming board.   I have data at the level of US Counties (level 1) nested within their respective State (level 2) and I have both predictors at the county level and the state level. My understanding was always that Proc Mixed determines the level of the variable in the model based on whether there is variability at each level. In this example, I have the population of the county (pop10) as a predictor and the way the state votes relative to others (CPVI), both ratio scales. My syntax is below:   proc mixed data = sor covtest ; class STATE ; model SORgc = pop10 CPVI /s DDFM=sat ; random int / sub=STATE ; ods output SolutionR = Res2; run;   The ODS output gives me:   WARNING: Output 'SolutionR' was not created. Make sure that the output object name, label, or path is spelled correctly. Also, verify that the appropriate procedure options are used to produce the requested output object. For example, verify that the NOPRINT option is not used.   because there are no level 2 residuals and the degrees of freedom suggest it is treating my level 2 variable CVPI as a level 1 predictor. I've attached the data file. I've checked that there is no variance in the variables at the state level (see second tab in excel sheet) and made sure everything is a number and everything I can possibly think of. SAS is doing the grouping right because it shows the number of subjects correctly (not all states are included).  Am I missing something really obvious? The degrees of freedom for a level 2 predictor should be less than the number of level 2 groups, right? I'm not going insane?       ... View more