Randomized controlled trials have proliferated in education, in part because they provide an unbiased estimator for the causal impact of interventions. It is increasingly recognized that many such trials in education have low power to detect an effect if indeed there is one. However, it is less well known that low powered trials tend to…

The purposes of this manuscript are to identify common statistical mistakes in sport management, and to provide scholars with suggestions on how to develop and improve the quality of quantitative research. We have reviewed articles published from 2001 to 2017 in the "Journal of Sport Management," "Sport Management Review,"…

Multivariate analysis of variance (MANOVA) is a statistical method used to examine group differences on multiple outcomes. This article reports results of a review of MANOVA in gifted education journals between 2011 and 2017 (N = 56). Findings suggest a number of conceptual and procedural misunderstandings about the nature of MANOVA and its…

Missing data are a persistent problem in psychological research. Peer nomination data present a unique missing data problem, because a nominator's nonparticipation results in missing data for other individuals in the study. This study examined the range of effects of systematic nonparticipation on the correlations between peer nomination data when…

Null hypothesis significance testing (NHST) has been the subject of debate for decades and alternative approaches to data analysis have been proposed. This article addresses this debate from the perspective of scientific inquiry and inference. Inference is an inverse problem and application of statistical methods cannot reveal whether effects…

This brief paper introduces a new approach to assessing the trustworthiness of research comparisons when expressed numerically. The 'number needed to disturb' a research finding would be the number of counterfactual values that can be added to the smallest arm of any comparison before the difference or 'effect' size disappears, minus the number of…

Given the American Psychological Association's strong recommendation to always report effect sizes in research, scholars have a responsibility to provide complete information regarding their findings. The purposes of this study were to (a) determine the frequencies with which different effect sizes were reported in published, peer-reviewed…

Because of the Flynn effect, IQ scores rise as a test norm ages but drop on the introduction of a newly revised test norm. The purpose of the current study was to determine the impact of the Flynn effect on learning disability (LD) diagnoses, the most prevalent special education diagnosis in the United States. Using a longitudinal sample of 875…

This "What Works Clearinghouse Procedures and Standards Handbook (Version 3.0)" provides a detailed description of the standards and procedures of the What Works Clearinghouse (WWC). The remaining chapters of this Handbook are organized to take the reader through the basic steps that the WWC uses to develop a review protocol, identify…

This article reviews the literature on interventions targeting the academic performance of students with attention-deficit/hyperactivity disorder (ADHD) and does so within the context of the statistical significance testing controversy. Both the arguments for and against null hypothesis statistical significance tests are reviewed. Recent standards…

Classic parametric statistical significance tests, such as analysis of variance and least squares regression, are widely used by researchers in many disciplines, including psychology. For classic parametric tests to produce accurate results, the assumptions underlying them (e.g., normality and homoscedasticity) must be satisfied. These assumptions…

Three criticisms of conventional uses of structural significance testing are elaborated; and alternatives for augmenting statistical significance tests are reviewed, which include emphasizing effect size, evaluating statistical significance in a sample size context, and evaluating result replicability. Among ways of estimating result…

Problems inherent in relying solely on statistical significance testing as a means of data interpretation are reviewed. The biggest problem with statistical significance testing is that researchers have used the results of this testing to ascribe importance or meaning to their studies where such meaning often does not exist. Often researchers…

Researchers increasingly recognize that significance tests are limited in their ability to inform scientific practice. Common errors in interpreting significance tests and three strategies for augmenting the interpretation of significance test results are illustrated. The first strategy for augmenting the interpretation of significance tests…

If the quantitative result of a study is observed only when the mean difference is statistically significant, the observed mean difference, variance, and effect size are biased estimators of corresponding population parameters. The exact distribution of sample effect size and the maximum likelihood estimator of effect size are derived. (Author/BW)