All -- I'm attempting to run a repeated measures ANOVA using proc glm. The problem I'm encountering is that I'm getting pathological estimates (or no estimates) of the the main effect for one of the repeated factors and the interactions involving that factor. The data consist of a between-subjects factor (Group) and two within-subjects factors Response_Type and Stage, each with two levels. Here is the section of code that I've written for the analysis:
/* --- code starts here --- */
/* --- code ends here --- */
I first print out the data set to see if there are any obvious problems, and then runs the repeated measures ANOVA. I've attached the section of the listing that is produced.
In the printout of the data set, I don't see any obvious problems other than one subject missing data for the dependent variables (frn1-frn4). glm produces the Tukey tests for the effect of Group for each of the variables, the number of observations is correct, the repeated measures level information is correct, but the information for the main effect of Response_Type and the interactions involving Response_Type are all missing. The estimate of the main effect of Group is provided, the estimate of the main effect of stage is provided, but anything involving Response_Type is blank. I've never run into this problem with proc glm, and this code works with a different data set that has the same structure, which suggests that there is something "wrong" with this data set. But I don't see anything obvious.
Can anyone provide any insight into this? My thanks in advance,
This is expected. That's how SAS has chosen as the default to handle categorical factors, one level will not get estimated. I wrote a brief explanation: https://communities.sas.com/t5/Statistical-Procedures/Interpreting-Multivariate-Linear-Regression-wi...
Thanks again, and problem solved: it turned that there was an error in the creation of the data file, such that the values for every observation across the two levels of the factor in question were identical. Fixed that error and now everything works as it should.
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