An explanation of the misuse of statistical significance testing and the true meaning of "significance" is offered. Literature about the criticism of current practices of researchers and publications is reviewed in the context of tests of significance. The problem under consideration occurs when researchers attempt to do more than just establish…

Use of "special" orthonormal mean contrasts and mean contrast variances can help educational researchers interpret a wide variety of repeated measures data. Most statistical packages allow educational researchers to test for differences across repeated measures using both the univariate mixed model F test and a multivariate test.…

This paper reviews criticism on misinterpretation and overuse of significance testing in the social sciences and examines use of effect size measures to enhance interpretation of significance testing. Review of typical effect size measures and their application is followed by analysis of use of effect size measures in studies reported over 10…

This article first outlines the logic of null hypothesis testing and the problems of using it to evaluate special education research. It then presents three alternative metrics, a binomial effect size display, a relative risk ratio, and an odds ratio, that can better identify important treatment effects using illustrative data from recently…

This paper focuses on two methods of performing multiple comparisons (post hoc or unplanned versus a priori or planned) for determining exactly where statistically significant results arise when there are more than "k equals two" groups. Textbook views and recommendations regarding the use of these two types of multiple comparisons are…

A growing controversy surrounds the strict interpretation of statistical significance tests in social research. Statistical significance tests fail in particular to provide estimates for the stability of research results. Methods that do provide such estimates are known as invariance or cross-validation procedures. Invariance analysis is largely…

A dichotomous dependent variable is used to determine a combination of variables that will predict group membership. Dichotomous variables are frequently encountered in multiple regression analysis. However, several textbooks question the appropriateness of using multiple regression analysis when analyzing dichotomous dependent variables. The…

An approach to statistical testing, which combines Neyman-Pearson hypothesis testing and Fisher significance testing, is recommended. The use of P-values in this approach is discussed in some detail. The author also discusses some problems which are often found in introductory statistics textbooks. The problems involve the definitions of…

Arguing that reliable and valid dropout rate estimates are prerequisite to establishment of causal factors and intervention programs, this article examines differences in definitions of dropouts, computational methods, and the complexities in defining cohorts, as well as the importance of sample attrition. Several sources of error are discussed.…

The purpose of this study was to investigate the effectiveness of computer-aided instruction as compared with the traditional lecture method of cognitive learning of new curriculum materials. It was hypothesized that students instructed by the computer-aided instruction method would gain higher knowledge of the subject matter in terms of cognitive…