Misuse of multivariate analysis of variance in behavioral research: the fallacy of the "protected" F test.
Researchers who examine multiple outcome variables sometimes invoke a multivariate analysis of variance approach known as the "protected F test" to control for experimentwise Type I error rate. Unfortunately, this procedure affords protection against experimentwise Type I error only in rare instances. The purpose of the present paper is to present the case against the protected F test and to discuss alternative methods of controlling for Type I error, including the Bonferroni adjustment and descriptive discriminant analysis. The latter approach is briefly elaborated as a truly multivariate solution for multivariate phenomena. The author cites multiple examples of proper and improper use of multivariate analysis of variance in research on child development.
Kellow
J T
JT
University of Houston-Clear Lake, TX 77056, USA. tkellow@pdq.net
D001525:Behavioral Sciences / Q000706:statistics & numerical data*; D016002:Discriminant Analysis; D006801:Humans; D015999:Multivariate Analysis; D011584:Psychology / Q000706:statistics & numerical data; D012106:Research / Q000706:statistics & numerical data; D012107:Research Design / Q000592:standards*