Good afternoon, I am trying to run a multivariate analysis using proc mixed as part of my dissertation work. The purpose of this analysis is to determine if temperature (temp) effects several metabolic parameters (var) for fish. Each individual is identified in the dataset (number) and a condition factor (k) is also included. I have managed to code a working model but when I look at the LS Means output, things do not make sense. I have 5 responses that are on different scales and while the estimates for the LSMs look reasonable, the standard errors are very similar across all responses and the DFs are incredibly high (168 when I sampled 48 individuals). I have tried finding help online but have not been successful. I'm not sure if the issue with the analysis is something in the code or in the way the data is set up. Any thoughts or suggestions are appreciated. I've pasted the model code here and attached some of the data as well. Thanks, Ben proc mixed data=mva.data3(where=(species='spot')) method=reml order=data; class var number temp; model y = var var*temp var*k / noint solution outp=mva.spot_out; random number; lsmeans var*temp / CL; *order is var then temp; run;
... View more