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I'm running a two way repeated measures ANOVA, and I'm having trouble finding what is the appropriate output to report (Contrasts vs Pairwise Comparisons).

I have a 2x5 design. Lets say I have Variable 1(group 1 and 2) and Variable 2 (groups a,b,c,d,e). I want to assess whether there is a difference in means based on separating data by variable 1 (group 1 vs group 2), variable 2 (a vs b vs c vs d vs e), or an interaction of both (1a vs 1b..etc).

However, I am haven't found much written on whether within-subject contrasts or pairwise comparisons are more appropriate to report after I found significant differences.

For instance, I found that means are significantly different between groups a,b,c,d,e. However, I now want to know WHERE the difference is (for instance is a larger b, etc).

Thank you for the help.

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  • $\begingroup$ Then you are looking for post-hoc comparisons, which is well covered on this site. $\endgroup$
    – chl
    Oct 31, 2020 at 19:25

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Functionally, they operate similarly.

From this page (demo in SPSS)

http://www.uvm.edu/%7Edhowell/StatPages/More_Stuff/RepMeasMultComp/RepMeasMultComp.html

Throughout this document I use the words Comparison and Contrast interchangeably. For what we are doing, they mean the same thing. I thought that I ought to spell that out to avoid confusion.

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  • $\begingroup$ In post-hoc comparisons following ANOVA, you either correct the test statistic (e.g., Tukey HSD) or the p-value (e.g., LS means or Bonferroni correction), to make the test less liberal. Further, repeated measures suggest a very specific design where you need to account for the matrix-covariance matrix. I believe this answer could be improved by discussing these two different issues. $\endgroup$
    – chl
    Oct 31, 2020 at 19:30

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