GLME analysis - how to compute the interaction effects between two variables?
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I have a dat set with two independent variables (predictor variables) with 3 levels each:
- IV 1 (time) = pre, during, post
- IV 2 (treat) = A, B, C
I used this formula to set my GLME
GLM_tbl_all.subject = nominal(GLM_tbl_all.subject);
GLM_tbl_all.time = categorical(GLM_tbl_all.time);
GLM_tbl_all.treat = categorical(GLM_tbl_all.treat);
GLM_outcome = fitglme(GLM_tbl_all, 'DV ~ time*treat + (1|subject)')% setting the subject as the grouping variable
However, because my variables have 3 levels each, I am having trouble understanding the outcome table.
i am interested to see whether there was a significant difference between time*treat interaction. But I only receive an output with the first column (names) looking like this:
(intercept)
during
post
B
C
during:B
post:B
during:C
Now I wonder, where can I find the field. that simply says time:treat ?
And I do not mean the specific pairwise comparisson, that I will do in the post hoc test. But in general whethere there is an interaction effect to begin with.
I think the problem is, that my factors have more than two levels maybe?
I appreaciate any help to learn!
Thank you
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