I have a within subjects design with 4 DVs and I ran a repeated measures analysis on SPSS. My DV is a physiological measurement and is not expected to be linear.
My multivariate Wilks lambda is significant at p = .004 and my Mauchly test approaches significance at p = .054. However, my univariate tests of within subjects is non-significant (uncorrected p =.07 and greenhouse Geisser p = .082)
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Given that my sphericity test is almost significant and given that I do not expect linearity in the data, is it reasonable to look at my multivariate test and ignore the non-significant univariate test?
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Do I even have to look at univariate if the multivariate is significant? I.e., am I justified to look at my pairwise comparisons simply because the multivariate is significant?
Best Answer
Multivariate tests for repeated-measures data are seldom, at least in published results in the experimental psychology I regularly read. Nevertheless there are recommendation for these tests. Most notably (from the top of my head):
O’Brien, R. G., & Kaiser, M. K. (1985). MANOVA method for analyzing repeated measures designs: An extensive primer. Psychological Bulletin, 97(2), 316–333. doi:10.1037/0033-2909.97.2.316
Algina, J., & Keselman, H. J. (1997). Detecting repeated measures effects with univariate and multivariate statistics. Psychological Methods, 2(2), 208–218. doi:10.1037/1082-989X.2.2.208
Keselman, H. J., Algina, J., & Kowalchuk, R. K. (2001). The analysis of repeated measures designs: A review. British Journal of Mathematical and Statistical Psychology, 54(1), 1–20. doi:10.1348/000711001159357
(I specifically liked the last one, Keselman et al., 2001)
You might also want to have a look at the multivariate statistics book by Tabachnik and Fidell.
It would be surprising if you couldn't find the recommendation for using the multivariate and ignoring the other (unfortunately nonsignificant) tests in your case in these papers.