I´m trying to learn generalized mixed models in SAS and I have now bumbed into a situation that I cannot figure out by myself. So I was thinking that maybe some of you could help me forward.
I´m running a model where I have normally distributed measurements of traits like tarsus etc in birds from different populations. I have few fixed factors (sampling area, sex and year) and their interactions in the model and random term "sampling site clustered within the sampling area" (2 sampling areas with both 2 sampling sites). I´m using SATTERTH as a method for computing the denominator degrees of freedom.
My problem is that for one particular trait I get really low degrees of freedom always when the sampling site is in the model, and for that particular factor. I noticed that playing around with the methods of computing the degrees of freedom, I can get "better" results, but I cannot understand why in this model, one fixed factor eats up my degrees of freedom.
If anyone can and would like to explain to me why this happens and how I should select the method for computing the DDF´s in "dummies" way, it would make my day. I'm happy to provide you with more information, I was not certain how I should present my problem.
Thank you in advance.