How do I build a Repeated Measures ANOVA model?

[#1]

Hi, I'm having trouble with statistical analyses. My dataset includes antibody data at multiple time points and I'm studying how genetic differences affect their response to vaccine. I built a repeated measures anova mixed model with unstructured covariance and it included time, age, gender, priming vaccine, 8 polymorphisms, and the crossover of these 8 polymorphisms with time, age, gender, and priming vaccine. I've run into a problem when doing posthoc multiple comparisons where "All pairwise comparisons mean-mean scatterplot cannot be shown because confidence intervals cannot be computed." Someone has suggested about the degrees of freedom being exhausted. I was wondering if anyone knows how to solve it or if I need to change my model? Thanks!

[#2]

Welcome!  It should be easy for you to verify if you have no df left for error ("exhausted" your df).  Just count up your model total df's, and if that total df = N-1 (N=total sample size) then you, indeed, have no df left for error. If that is the case, your model will have to be reduced in some way; which way? That is a question that would take a more involved discussion.  That said, you may have over-specified your model (e.g., too many interactions). But, as I suggest, it will take a more involved discussion to tease this apart.       

[#3]

Multiple comparison correction methods, such as the Bonferroni method, the Holm method, or the Benjamini-Hochberg method, can be used to address this problem. These methods reduce the likelihood of false positives by applying a significance level correction to each test. If you have already used one of these methods and still encounter a problem, it is possible that the problem is related to the exhaustion of degrees of freedom. In that case, you may need to modify your model and use a simpler model with fewer variables.