Analyses of data are presented to illustrate the advantages of using a priori or planned comparisons rather than omnibus analysis of variance (ANOVA) tests followed by post hoc or posteriori testing. The two types of planned comparisons considered are planned orthogonal non-trend coding contrasts and orthogonal polynomial or trend contrast coding.…

The general problem of measuring the association between an independent nominal-scaled variable X and a dependent variable Y whose scale of measurement may be interval, ordinal, or nominal is discussed. (Author/RC)

A series of independent, normally distributed events may be broken into intervals on an a priori basis. Then, within interval variance may be compared to among interval variance. These might be considered short-term and long-term variances. This concept and a test for comparing variances are presented. (Author/JKS)

Two potentially useful tests for homogeneity of variance--the jackknife test and the Box test--are described and compared. Recommendations for the use of these techniques and computational examples of each are provided. (Author/JKS)

Two sampling studies were run to determine the robustness of the several tests of homogeneous variances to deviations from normality, and to compare the power of these tests. (Authors)

The conduct of multiple post hoc comparison procedures following an analysis of variance is discussed. Various procedures are contrasted in terms of appropriateness, power, and other features. Octhogonal and nonorthogonal comparisons are discussed. (JKS)

Several ways of using traditional analysis of variance to test the homogeneity of variance in factorial designs with equal or unequal cell sizes are compared using theoretical and Monte Carlo results. (Author/JKS)

Researchers are often in a dilemma as to whether parametric or nonparametric procedures should be cited when assumptions of the parametric methods are thought to be violated. Therefore, the Kruskal-Wallis test and the ANOVA F-test were empirically compared in terms of probability of a Type I error and power under various patterns of mean…

The Dunnett procedure for comparing several treatment means with a control is applied to the problem of comparing several treatment variances with the variance of a control. Appropriate critical values are specified and an example is provided. (Author)

Two alternative procedures are described for testing the significance of differences of group means. The first consists of a reduction in the critical value when comparing the largest and smallest means. The other alternative uses the unmodified range test without a preliminary F test. An example is provided. (Author/CTM)

Three techniques for estimating Kuder Richardson reliability (KR20) coefficients for incomplete data are contrasted. The methods are: (1) Henderson's Method 1 (analysis of variance, or ANOVA); (2) Henderson's Method 3 (FITCO); and (3) Koch's method of symmetric sums (SYSUM). A Monte Carlo simulation was used to assess the precision of the three…

The problem that this research addressed was one of decision making. Given three sets of criterion-referenced tests which were designed to be parallel in content, would a traditional reliability coefficient produce different decisions about the reliability of those tests than would kappa? The procedure used collected statewide results on 136 test…

Monte Carlo techniques were employed to compare the familiar F-test with Welch's V-test procedure for testing hypotheses concerning a priori contrasts among K treatments. The two procedures were compared under homogeneous and heterogeneous variance conditions. (Author)

Dunnett's procedure for comparing K-1 treatments with a control is discussed within the context of three nonparametric models: those of Kruskal-Wallis, Friedman, and Cochran. (Author/MH)