This computer simulation study evaluates the robustness of the nonparametric Levene test of equal variances (Nordstokke & Zumbo, 2010) when sampling from populations with unequal (and unknown) means. Testing for population mean differences when population variances are unknown and possibly unequal is often referred to as the Behrens-Fisher…

Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…

Whenever one uses a composite scale score from item responses, one is tacitly assuming that the scale is dominantly unidimensional. Investigating the unidimensionality of item response data is an essential component of construct validity. Yet, there is no universally accepted technique or set of rules to determine the number of factors to retain…

The central messages of this paper are that (a) unequal variances may be more prevalent than typically imagined in educational and policy research, and (b) when considering tests of equal variances one needs to be cautious about what is being referred to as "Levene's test" because Levene's test is actually a family of techniques. Depending on…

A computer simulation compared significance tests of correlation coefficients calculated from initial scores, from ranks assigned by the Spearman method, and from three kinds of modified ranks. Implications of findings for the idea that rank correlation is a nonparametric correlation method are discussed. (SLD)

A modified "F" test is derived that includes a correction for nonindependence of between-groups and within-groups sample values in analysis of variance (ANOVA) designs. Computer simulations based on normal and nonnormal distributions illustrate the usefulness of the approach, which was more powerful than conventional within-subjects…

Comparisons of the Wilcoxon test, Friedman test, and repeated-measures analysis of variance (ANOVA) on ranks in a computer simulation show that the Friedman test performs like the sign test whereas the ANOVA performs like the Wilcoxon test. Classification of these tests in introductory statistics textbooks should be revised. (SLD)