Personal preference--I would never do a repeated measures in time (longitudinal design) in GLM, as the restrictions on the covariance structure are not reflective of physical, biological or economical processes. The sphericity assumption and the work-around Huynh-Feldt or Greenhouse-Geisser adjustments all assume an "exchangeable" structure--that the actual ordering of the time variables makes no difference in the error. Advances in methodology mean that we do not have to make such simplifying assumptions. For similar reasons, I would not use GLM for random effects analyses. I use GLM for regression when there are class variables, and for multivariate ANOVA. Otherwise, I use GLIMMIX--it handles almost everything available in MIXED, plus it can deal with non-normally distributed endpoints. Steve Denham
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