Hello, I am new to SAS and I am having trouble figuring out the difference between proc glimmix and proc panel in the context of panel data analysis. I have an unbalanced panel (CUSTOMER_ID + TIME_PERIOD) and I want to capture unobserved heterogeneity at customer-level, using a random effects model. PROC GLIMMIX: I am specifcying a VC type covariance matrix between different customers. That is, I expect observations from the same customer to be correlated across time periods but not across different customers. All customers in addition have an idiosyncratic error component. PROC GLIMMIX DATA=BK.DATA1;
CLASS VAR1 CUSTOMER_ID;
MODEL Y = VAR1 VAR2 VAR3 VAR1*VAR3
/LINK = IDENTITY DIST = NORMAL SOLUTION;
RANDOM INTERCEPT/ SUBJECT = CUSTOMER_ID TYPE= VC V;
RUN; PROC PANEL: For the same covariates as in the above model, I am running in to trouble. For example, I do not get the Hausman test result and multicollinearity problems. PROC PANEL DATA=BK.DATA1;
CLASS VAR1 ;
MODEL Y = VAR1 VAR2 VAR3 VAR1*VAR3
/RANONE VCOMP = FB;
ID CUSTOMER_ID TIME_PERIOD;
RUN; I have the following questions: 1. What are the differences in the modeling assumptions between using proc glimmix and proc panel? Aren't they the same (as GLS/FGLS) for a linear model with a single random effect? If so, shouldn't they give identical estimates? I understand that proc glimmix uses GEE, but specifying normal distribution should be the same as GLS, right? 2. Is proc glimmix "better than" proc panel in some sense? Or do they both do very different things (in the case of panel data) and may be, I am completely missing something here. I would highly appreciate your comments. BK
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