Researchers often use the analysis of variance to test hypotheses about the means, followed by a multiple comparison technique when the F-test is significant. The technique is this study was developed by Newman (1939) and Keuls (1952). A flaw in the rationale underlying this technique was evaluated to determine whether the flaw is sufficiently…

The purposes of this paper are to: (1) describe some of the serious shortcomings in the current use of tests of statistical significance, (2) discuss how misuses are perpetuated in some widely used references, and (3) present an alternative significance testing model that overcomes some, but not all, of the shortcomings of the currently used…

Focuses on the procedures available for substituting a special predictive coding method for some of the more complex general regression procedures. (Author)

The use of planned, or "a priori," and unplanned, or "post hoc," comparisons to isolate differences among means in analysis of variance research is discussed. Planned comparisons typically involve weighting data by sets of "contrasts." Planned comparison offer more power against Type II errors. In addition, they force…

Techniques for detecting synergistic effects in analysis of variance designs are presented and discussed. These techniques make it possible to apply some kinds of theoretical insights to the data analysis phase of a study: either by seeking synergistic effects implied or predicted by theory, or by seeking evidence of synergies as alternative…

Games (1973) criticized the Marascuilo and Levin (1970) "nested" or simple effects design as a poor substitute for the usual logic of a factorial analysis of variance. Marascuilo and Levin's use of "nesting" is completely idiosyncratic and contrary to well-established usage, thus confusing the student. Proper usage is…

Intended for use on Conversational Monitor System (CMS), the Tukey FORTRAN program facilitates pairwise comparisons among means following a significant Fratio in an analysis of variance. Tukey's statistic can be obtained by entering information regarding the design and analysis of variance results. Two variations are also available. (Author/BS)

See EJ 041 277 for original article. (DG)

Twelve multiple comparison tests, both simultaneous and sequential, are described, analyzed, and evaluated. Overall recommendations are presented in a flow-diagram. (DG)

This nonparametric analysis of variance program includes the Kruskal-Wallis, Friedman, and Cochran methods. (DG)

Analyses of artificial data involving repeated, related binary measures to different samples suggest that Tideman's generalized chi-square statistic and conventional repeated-measures analysis of variance do not produce conflicting outcomes. Provided the appropriate assumptions are met, analysis of variance may provide a more versatile approach.…

Hollingsworth recently showed a posttest contrast for analysis of variance situations that, for equal sample sizes, had several favorable qualities. However, for unequal sample sizes, the contrast fails to achieve status as a maximized contrast; thus, separate testing of the contrast is required. (Author/GSK)

Describes a set of five programs providing robust techniques that work well when the assumption of conventional analysis of variance have been violated. (Author/RC)