There are three main ways you can approach analyzing repeated measures data, assuming the dependent variable is measured 
continuously: repeated measures ANOVA, Mixed Models, and Marginal Models. Let’s take a look at how the three approaches differ and some of their advantages and disadvantages.
For a few, very specific designs, you can get the exact same results from all three approaches. This makes it difficult to figure out what each one is doing, and how to apply them to OTHER designs.
For the sake of the current discussion, I will define repeated measures data as repeated measurements of the same outcome variable on the same individual. The individual is often a person, but could just as easily be a plant, animal, colony, company, etc. For simplicity, I’ll use “individual.” (more…)