Hidden multiplicity in multiway ANOVA: Prevalence, consequences, and remedies. Prevalence and remediesCramer, A. O. J., van Ravenzwaaij, D., Matzke, D., Steingroever, H., Wetzels, R., Grasman, R. P. P. P., Waldorp, L. J. & Wagenmakers, E-J., Apr-2016, In : Psychonomic Bulletin & Review. 23, 2, p. 640-647 8 p.
Research output: Contribution to journal › Article › Academic › peer-review
Many psychologists do not realize that exploratory use of the popular multiway analysis of variance harbors a multiple-comparison problem. In the case of two factors, three separate null hypotheses are subject to test (i.e., two main effects and one interaction). Consequently, the probability of at least one Type I error (if all null hypotheses are true) is 14 % rather than 5 %, if the three tests are independent. We explain the multiple-comparison problem and demonstrate that researchers almost never correct for it. To mitigate the problem, we describe four remedies: the omnibus F test, control of the familywise error rate, control of the false discovery rate, and preregistration of the hypotheses.
|Number of pages||8|
|Journal||Psychonomic Bulletin & Review|
|Early online date||15-Sep-2015|
|Publication status||Published - Apr-2016|
- FALSE DISCOVERY RATE, BONFERRONI PROCEDURE, REGISTERED-REPORTS, STATISTICAL POWER, DESIGN, TESTS
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