Several programs of research have sought to assess the replicability of scientific findings in different fields, including economics and psychology. These programs attempt to replicate several findings and use the results to say something about large-scale patterns of replicability in a field. However, little work has been done to understand the…

Researchers commonly interpret effect sizes by applying benchmarks proposed by Cohen over a half century ago. However, effects that are small by Cohen's standards are large relative to the impacts of most field-based interventions. These benchmarks also fail to consider important differences in study features, program costs, and scalability. In…

The article provides perspectives on p values, null hypothesis testing, and alternative techniques in light of modern robust statistical methods. Null hypothesis testing and "p" values can provide useful information provided they are interpreted in a sound manner, which includes taking into account insights and advances that have…

Data transformations have been promoted as a popular and easy-to-implement remedy to address the assumption of normally distributed errors (in the population) in linear regression. However, the application of data transformations introduces non-ignorable complexities which should be fully appreciated before their implementation. This paper adds to…

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 paper examines sources of potential bias in systematic reviews and meta-analyses which can distort their findings, leading to problems with interpretation and application by practitioners and policymakers. It follows from an article that was published in the "Canadian Journal of Communication" in 1990, "Integrating Research…

Overlap-based measures are increasingly applied in the synthesis of single-subject research. This article considers two criticisms of overlap-based metrics, specifically that they do not measure magnitude of effect and do not adequately correspond with visual analysis. It is argued that these criticisms are based on fundamental misconceptions…

The Journal of Agricultural Education (JAE) requires authors to follow the guidelines stated in the Publication Manual of the American Psychological Association [APA] (2009) in preparing research manuscripts, and to utilize accepted research and statistical methods in conducting quantitative research studies. The APA recommends the reporting of…

Null hypothesis significance testing has dominated quantitative research in education and psychology. However, the statistical significance of a test as indicated by a p-value does not speak to the practical significance of the study. Thus, reporting effect size to supplement p-value is highly recommended by scholars, journal editors, and academic…

The authors critiqued the M. K. Lovelace (2005) meta-analysis of the Dunn and Dunn Model of Learning-Style Preferences (DDMLSP). The conclusion that Lovelace reported in her meta-analysis that learning-style instruction is a beneficial form of instructional delivery is unjustified because of critical conceptual and practical problems. Those…

Why methodologists encourage the use of magnitude-of-effect (ME) indices as research interpretation aids is discussed, and different types of ME estimates are reviewed. Correction formulas developed to alternate statistical bias in ME estimates are also discussed, and their effects are illustrated. (SLD)

This paper examines the problems caused by relying solely on statistical significance tests to interpret results in contemporary social science. The place of significance testing in educational research has often been debated. Among the problems in reporting statistical significance are questions of definition and terminology. Problems are also…

Problems with using stepwise analytic methods are discussed, and better alternatives are illustrated. To make the illustrations concrete, an actual data set, involving responses of 91 medical school admissions directors to 30 variables, was used. The 30 variables involved perceptions of barriers to medical school with respect to characteristics of…