Dear StatsMan   Many thanks for your response! Indeed, that it is my experience, PROC MIXED keeps the uncomplete cases in an Anova respeated measures, but PROC GLM is not. It is nice to know the reason behind (MLE in PROC MIXED, and MoM in PROC GLM) the discrepancy.    When you said "PROC ANOVA requires balanced data in the design, PROC GLM and PROC MIXED do not." are you refering to a Pre-post design (and no repeated measures in the middle) ? Why the diferences between  PROC GLM and PROC ANOVA in this context?   Do you know what is PROC ANOVA expected to do in an Anova repeated measures when uncomplete cases are observed?   Thanks in advance Philippe   ... View more

Dear Paige  Many thanks for your prompt reponse.  My understanding is that balanced and unbalanced data is a term equivalent for complete/uncomplete cases.   "A repeated measures ANOVA requires a balanced number of repeated measurements for each experimental unit. Due to this requirement, experimental units with missing measurements are completely excluded from the analysis" (Guidelines for repeated measures statistical analysis approaches with basic science research considerations - PMC (nih.gov))    When I said the "the unbalanced observations [are] not being included in the model" is a similar statement than previous guideline paper saying  "[the] missing measurements are completely excluded from the analysis". This is a behaviour that I would expect to see in any Anova model process. I wonder if this could be done in PROC MIXED, since the way I am fitting the model is keeping the unbalanced observation (uncomplete cases) in the model. Please see below the used code:   proc mixed data = DATA_ANOVA; class ID TRT VISIT ; model chg = TRT TRT*VISIT / solution cl; repeated / subject=ID type = AR(1); run;   Thanks in advance Philippe       ... View more