I have a dataset and our dependent variable is measured at five different time points. we want to know if there is a difference between the two groups that we are studying (control and experimental). We also want to know if the dependent variable response is changing over time.
I found from various resources that a mixed model approach would be appropriate for my analysis. However, I would like to know what is the difference in the test statistic between the mixed models and repeated measures ANOVA (GLM)? do both these approaches use F-test for testing the significance effect? is there any difference in the way F-test statistic is computed between these two approaches?
The topic of repeated measures is large and complex, and I don't think the discussion forum can really address all the issues that you need to consider. The approach to repeated measures in GLM is very different from the mixed-model approach (such as in MIXED or GLIMMIX). I recommend you read: http://www.ats.ucla.edu/stat/sas/library/mixedglm.pdf
by Russ Wolfinger and co-author. It is now somewhat out of date (lots of new features in MIXED, etc.), but this may get you started.