Remarkability is introduced as a quantifiable attribute of given data and as a basis upon which one may rationally judge its scientific value. Applications of remarkability theory to various research and statistical problems and procedures are discussed. (DG)

Monte Carlo results were used to evaluate procedures for discriminating between groups. A multiple testing version of Hotelling's T-squared and the Bonferroni procedure were most powerful for detecting at least one true difference, depending on conditions examined. A multiple Bonferroni procedure was superior in power for detecting all true…

Practical formulas for several analysis of variance (ANOVA) designs and models are presented which make it possible for readers to compute strength of association measures without the use of complete ANOVA tables. (Author/PN)

Points out that 108 studies in the first 25 volumes of AV Communication Review used univariate analysis of variance to test experimental hypotheses, and suggests that researchers include omega-squared values in their reports to permit estimation of the relationship between x and y variables, and correlation data for comparing studies. (MER)

Suggests six analytic areas for dual-career research (marriage type, domestic responsibility, satisfaction, self-image, career salience, and career line); provides questions for a large-scale survey research project; and analyzes scale types. The scales provide useful direction for dual-career family research. (Author)

Three nonparametric alternatives to the parametric Bartlett test are presented for handling the K-sample equality of variance problem. The two-sample Siegel-Tukey test, Mood test, and Klotz test are extended to the multisample situation by Puri's methods. These K-sample scale tests are illustrated and compared. (Author/GDC)

Hawkin's procedure for testing a sequence of observations for a shift in location could have applicability for assessing change within a single subject. Monte Carlo results suggest that Hawkins' procedure is robust with respect to moderate violations of its underlying assumptions of homogeneity of variance and normality. (Author/GDC)

Errors of misclassification and their effects on categorical data analysis are discussed. The chi-square test for equality of two proportions is examined in the context of errorful categorical data. The effects of such errors are illustrated. A correction procedure is developed and discussed. (Author/MH)

A Monte Carlo approach was used to examine bias in the estimation of indirect effects and their associated standard errors. Results illustrate the adverse effects of nonnormality on the accuracy of significance tests in latent variable models estimated using normal theory maximum likelihood statistics. (SLD)

Refutes Peter Mueser's criticisms of the author's position on formalistic research approaches. Restates that statistical significance is virtually useless. Claims mathematical economists take their intellectual positions from mathematics departments bringing irrelevant intellectual values into economics. (NL)

Describes two invariance tests, the jackknife procedure and Procrustean rotation, and applies them in a discriminant analysis for this heuristic study. Invariance testing helps to prevent overemphasis on findings of statistical significance and overgeneralization of a research result, and thus is gaining favor as an indicator of result importance.…

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)

A brief overview is provided of the Conger-Lipshitz approach to estimating the reliability of a profile or test battery. A computational example from a recent study shows how canonical reliability can be obtained through existing statistical software. (SLD)

Twenty-eight books published from 1910 to 1949, 19 books published from 1990 to 1992, and 5 multiple edition books were reviewed to examine the presentations of statistical testing, particularly coverage of the p-value and fixed-alpha approaches. Statistical testing itself is not at fault, but some textbook presentations, testing practices, and…