Abstract
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.
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