Three articles in this special issue explore issues related to the use and misuse of statistical significance testing, the major methodological issue in current educational research. Comments on these articles and rejoinders by the authors of the first three articles explore additional aspects of statistical significance testing. (SLD)

Although statistical significance testing as the sole basis for result interpretation is a flawed practice, significance tests can be useful as one of three criteria that must be demonstrated to establish a position empirically. Statistical significance testing provides evidence that an event did not happen by chance but gives no evidence of the…

Expresses a "middle-of-the-road" position on statistical significance testing, suggesting that it has its place but that confidence intervals are generally more useful. Identifies 10 errors of omission or commission in the papers reviewed that weaken the positions taken in their discussions. (SLD)

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…

The use of directional and nondirectional hypothesis testing was examined from the perspectives of textbooks, journal articles, and members of editorial boards. Three widely used statistical texts were reviewed in terms of how directional and nondirectional tests of significance were presented. Texts reviewed were written by: (1) D. E. Hinkle, W.…

The controversy about the use or misuse of statistical significance testing has become the major methodological issue in educational research. This special issue contains three articles that explore the controversy, three commentaries on these articles, an overall response, and three rejoinders by the first three authors. They are: (1)…

Reviews null hypothesis statistical significance testing (NHST) in its historical context and concludes that workable alternatives to NHST are available. Among suggested alternatives, effect magnitude measures, replication techniques, and meta-analytic techniques are discussed. (SLD)

Attempts to clarify the positions of T. Nix and J. Barnette on statistical significance testing, advocates the routine use of effect size, and encourages reporting results in simple terms. (SLD)

Discusses commonalities in the papers of this special issue, addresses concerns about errors of omission expressed by T. Knapp, and provides some recommendations for the use of statistical significance testing with requirements for estimates of effect sizes. (SLD)

Misuses of null hypothesis significance testing are reviewed and alternative approaches are suggested for carrying out and reporting statistical tests that might be useful to program evaluators. Several themes, including the importance of respecting the magnitude of Type II errors and describing effect sizes in units stakeholders can understand,…

Considers reviews of L. Daniels's article on editorial policy regarding statistical significance testing and concludes that the controversy is not over, although the gradual movement toward requiring additional information in the reporting of statistical results is viewed as a positive trend. (SLD)

Comments on discussions of statistical significance testing in this special issue, placing the articles in the context of contemporary research literature. Empirical evidence is cited that suggests that the American Psychological Association's policy of encouraging effect size reporting has had no appreciable effect on the research literature.…

Offers a framework for remedying some of the problems associated with the use of statistical significance tests through modifying journal editorial policies. Reviews examples from some journals that have established guidelines for reporting results of statistical significance tests. (SLD)

Too few researchers understand what statistical significance testing does and does not do, and consequently their results are misinterpreted. This Digest explains the concept of statistical significance testing and discusses the meaning of probabilities, the concept of statistical significance, arguments against significance testing,…