Previous simulation studies of randomization tests applied in single-case educational intervention research contexts have typically focused on A-to-B phase changes in means/levels. In the present simulation study, we report the results of two multiple-baseline investigations, one targeting between-phase changes in slopes/trends and the other…

Building on previous arguments for why educational researchers should not provide effect-size estimates in the face of statistically nonsignificant outcomes (Robinson & Levin, 1997), Onwuegbuzie and Levin (2005) proposed a 3-step statistical approach for assessing group differences when multiple outcome measures are individually analyzed…

An alternative is proposed to the usual Interaction and Nested Analysis of Variance (ANOVA) models by which a researcher will be able to investigate both interaction and nested questions in the same experiment without committing Type IV errors. (RC)

Measurement error in dependent variables reduces the power of statistical tests to detect mean differences of specified magnitude. Procedures for determining power and sample size that consider the reliability of the dependent variable are discussed and illustrated. Methods for estimating reliability coefficients used in these procedures are…

Logically consistent hypothesis-testing for factorial analysis of variance designs is proposed in the context of a hierarchical model. It is shown that all of the hypotheses associated with the traditional factorial model are conceptually independent and occupy the lowest levels of the hierarchy. (Author/JKS)

In a recently reported study, the functional components of imagery and vocalization strategies in children's verbal discrimination learning were examined, following the combined experimental/correlational logic of Underwood. The present research extends those results to a strategy that (unlike imagery and vocalization) has a positive influence on…

Outlines concerns that must be addressed by those who advocate replacing statistical hypothesis-testing with alternative data-analysis strategies. Suggests that commonly recommended alternatives are not perfect and that various hypothesis-testing modifications can be implemented to make the process and its conclusions more credible. Hypothesis…

Comments (TM 503 706) on an earlier article (TM 503 420) concerning the comparison of the completely randomized design and the randomized block design are acknowledged and appreciated. In addition, potentially misleading notions arising from these comments are addressed and clarified. (See also TM 503 708). (Author/CTM)

Marascuilo and Levin's (1970) notion of Type IV errors is extended, with respect to the interpretation of interactions in analysis of variance (ANOVA) designs. To help clarity what an interaction is and what it is not, in terms of the ANOVA model, the following points are made: (i) interactions should be thought of as linear contrasts involving…

Textbook calculations of statistical power or sample size follow from formulas that assume that the variables under consideration are measured without error. However, in the real world of behavioral research, errors of measurement cannot be neglected. The determination of sample size is discussed, and an example illustrates blocking strategy.…

Because of criticisms leveled at statistical hypothesis testing, some researchers have argued that measures of effect size should replace the significance-testing practice. We contend that although effect-size measures have logical appeal, they are also associated with a number of limitations that may result in problematic interpretations of them…

Journal editors respond to criticisms of reliance on statistical significance in research reporting. Joel R. Levin ("Journal of Educational Psychology") defends its use, whereas William D. Schafer ("Measurement and Evaluation in Counseling and Development") emphasizes the distinction between statistically significant and important. William Asher…