Violation of the sphericity assumption in repeated-measures analysis of variance can lead to positively biased tests, i.e., the likelihood of a Type I error exceeds the alpha level set by the user. Two widely applicable solutions exist, the use of an epsilon-corrected univariate analysis of variance or the use of a multivariate analysis of variance. It is argued that the latter method offers advantages over the former.
Get full access to this article
View all access options for this article.
References
1.
BoikR. J. (1981) A priori tests in repeated measures designs: effects of nonsphericity. Psychometrika, 46, 241–255.
2.
BradleyJ. V. (1968) Distribution-free statistical tests. Englewood Cliffs, NJ: Prentice-Hall.
3.
DavidsonM. L. (1972) Univariate versus multivariate tests in repeated measures experiments. Psychological Bulletin, 77, 446–452.
4.
GeisserS.GreenhouseS. W. (1958) An extension of Box's results on the use of the F distribution in multivariate analysis. Annals of Mathematical Statistics, 29, 885–891.
5.
HuynhH.FeldtL. S. (1970) Conditions under which mean square ratios in repeated measurements designs have exact F distributions. Journal of the American Statistical Association, 65, 1582–1589.
6.
JenningsJ. R. (1987) Editorial policy on analyses of variance with repeated measures. Psychophysiology, 24, 474–475.
7.
KeselmanH. J.RoganJ. C. (1980) Repeated measures F tests and psychophysiological research: controlling the number of false positives. Psychophysiology, 17, 499–503.
8.
O'BrienR. G.KaiserM. K. (1985) MANOVA method for analyzing repeated measures design: an extensive primer. Psychological Bulletin, 97, 316–333.
9.
RoganJ. C.KeselmanH. J.MendozaJ. L. (1979) Analysis of repeated measurement. British Journal of Mathematical and Statistical Psychology, 32, 269–286.
10.
VaseyM. W.ThayerJ. F. (1987) The continuing problem of false positives in repeated measures ANOVA in psychophysiology: a multivariate solution. Psychophysiology, 24, 479–486.
