Criticizes an article in which S. A. Cohen and J. S. Hyman describe as "suspicious" the high proportion of statistically significant findings reported in published educational research journals and offers alternative explanations for the high statistical power reported. (GC)

A dialog between two fictional teachers provides some basic examples of how research that uses approved methodology may provide results that are significant statistically but not significant practically. (PGD)

The second half of a dialogue between two fictional teachers examines the significance of statistical significance in research and considers the factors affecting the extent to which research results provide important or useful information. (PGD)

Responds to Biskin's comments (this issue) on the significance test controversy. Highlights areas of agreement (importance of replication evidence, importance of effect sizes) and disagreement (influence of sample size, evaluation of populations vs. samples, significance of Carver's article). Includes further recommendations for reporting research…

Makes the case that science is best served when researchers focus on the size of effects and their practical significance. Advocates the use of confidence intervals for deciding whether chance or sampling variability is an unlikely explanation for an observed effect. Calls for more emphasis on effect sizes in the next edition of the American…

This commentary on EC 603 695 argues that significance testing is a necessary but insufficient condition for positivistic research, that judgment-based assessment and single-subject research are not substitutes for significance testing, and that sampling fluctuation should be considered as one of numerous epistemological concerns in any…

Three criticisms of overreliance on results from statistical significance tests are noted. It is suggested that: (1) statistical significance tests are often tautological; (2) some uses can involve comparisons that are not completely sensible; and (3) using statistical significance tests to evaluate both methodological assumptions (e.g., the…

This paper argues that judgment-based assessment of data from multiply replicated single-subject or small-N studies should replace normative-based (p=less than 0.05) assessment of large-N research in the clinical sciences, and asserts that inferential statistics should be abandoned as a method of evaluating clinical research data. (Author/JDD)

Presentation of quantitative research on the family often suffers from a tendency to interpret findings on a statistical rather than substantive basis. Advocates the use of data analysis that lends itself to an intuitive understanding of the nature of the findings, the strength of the association, and the import of the result. (JPS)