Unfortunately the instructions for the procedure that does it in SAS are incomprehensible to all but highly trained statisticians. No longer do you lose the entire data for a subject who missed one or two tests. You can dial up just about any structure of standard deviations and correlations. The data set is submitted in the more natural univariate format. The subject term in a repeated-measures model is a random effect.
Random effects produce variance that has to be accounted for in the model.
Link to them from the page devoted to Proc Mixed . Estimates or Contrasts OK, let's assume we've got a method that accounts for lack of sphericity. Now for the question of estimates or contrasts between the mean jump heights at the different times. Some stats programs offer standard contrasts. One level with every other , would be the obvious contrast to apply to post1 in the above example.