Hi all. I have two 2-level independent variables: Gender (0 and 1) and Group (0 and 1) and a continuous DV: Score. For my full model, I ran the following analysis: PROC GLM DATA = mydata;      CLASS Gender Group;      MODEL Score = Gender Group Gender*Group RUN; Just out of interest, I calculate an interaction between the two variables myself (by using this formula: "Interaction = Gender*Group") and ran this model: PROC GLM DATA = mydata;      CLASS Gender Group Interaction; *It makes no difference if "Interaction" is in the class section;      MODEL Score = Gender Group Interaction; RUN; The weird thing is that these produced different results! The results for the interaction were the same in each, but the individual main effects were very different. The reason that I am interested in this is that with PROC REG, the latter kind of model is the only possible one. And indeed, the results from PROC REG match the results from the second model above, and not the first (more automatic) one. What gives? Am I calculating the interaction incorrectly? Best, Fearghal ... View more

Hi all, I'm conducting a mixed ANOVA. I have an independent groups variable (Group) with 2 levels and a repeated measures variable (Time) with 4 levels. I want to see if there's a main effect of Group, a main effect of Time and/or an interaction between the two. In SPSS, this is simply done through the main ANOVA options. Because Group has only two levels, the analysis for the main effect of this variable is the same as doing a simple t-test. Indeed, in SPSS the exact same results come about for the Group part of the ANOVA as they do for a separate t-test (they both reveal Group to be non-significant). In SAS, I have been using the PROC MIXED statement to conduct the a mixed ANOVA with this exact code (for a dataset in Long Format): PROC MIXED DATA = MyData; CLASS Time Group IDSubject;   MODEL Score = Time Group Group*Time;   REPEATED Time/ SUBJECT = IDSubject; RUN; What's interesting is that the when I run this code, group is found to be significant! When I run a t-test using SAS, the results (non-significant) are the same as the t-test in SPSS and the main effect analysis for group in the Mixed ANOVA in SPSS as well. My question is, why am I getting a different result in the Mixed ANOVA in SAS compared with SPSS. I'm assuming it has something to do with different calculations since the PROC mixed seems to be used for other things like Multilevel modelling. I'd appreciate any help. ... View more

Hi all, I'm racking my brains trying to do a Factorial Repeated Measures ANOVA; something that I was able to do easily on SPSS (the new lab I've moved to uses SAS). I found a similar discussion to this on these treads, but it was never really concluded. I have three IVs, one is an independent group with two levels ("teen" and "adult") while the other two are repeated measures IVs with two levels each (Time: "0 Months" and "12 Months"; Task: "Task A" and "Task B".) So just to be clear, each of my participants belonged to one of two groups, but all participants completed task A and task B at 0 Months and 12 Months. I've found in the SAS documentation (and on other websites) how to conduct an ANOVA where one variable is a repeated measures one while the other variables are independent groups; it seems to be possible to do it in PROC GLM or PROC MIXED. However, I cannot see how to alter this syntax so as to incorporate an additional repeated measures variables; and to look at the interaction between the two repeated measures variables, i.e. I'd like to be able to say whether the difference between performance on task A and B is different at each time point. If I was just using one repeated measures variable (e.g. Time), I'd use the following code: PROC GLM DATA=MyData;   CLASS Age_Group;   MODEL Time1-Time2 = Age_Group;   REPEATED Time 2; RUN; ...but I can't see how to alter this to include another repeated measures IV. Is it the case that PROC GLM can only handle one Repeated Measures variable at a time and that I need to turn to PROC MIXED to do this? Hope the above makes sense! Fearghal ... View more