Hello Everyone! I am trying to run a MLM using "Proc mixed" (see code below). The model has a LEVEL 1 PREDICTOR which is identical for each subject. Specifically, people heard one of 8 different noise levels, and we subsequently tested reaction time to complete math problems. This noise level variable is an interval variable with possible values of 1,2,3,4,5,6,7,8. Importantly, I would like to let this level 1 predictor be random, so as to model individual differences in the IV/DV slope. My PROBLEM/question is that Proc Mixed seems to recognize the fact that there is no between-person variance in this predictor, and so appears to not be modeling individual differences in the IV/DV slope. I'll paste in the results for Covariance Parameter Estimates below, with the problem being the UN(2,2) parameter is not estimated. Am I correct in assuming SAS is not modeling individual differences in the IV/DV slope? And how can I coax it to model these effects? Thanks so much!! Robbie Covariance Parameter Estimates Cov Parm Subject Estimate StandardError Z Value Pr Z UN(1,1) Subject 0.02698 0.003031 8.9 <.0001 UN(2,1) Subject 2.10E-06 0.000257 0.01 0.9935 UN(2,2) Subject 0 . . . Residual 0.05797 0.000519 111.61 <.0001 PROC Mixed NOITPRINT NOCLPRINT COVTEST MAXITER=250; CLASS Subject; MODEL Math_reaction_time = Noise_level / SOLUTION DDFM=BW COVB NOTEST; RANDOM INTERCEPT Noise_level /SUB=Subject TYPE=UN; ODS EXCLUDE NOBS; RUN;
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