An alternative analysis of the two-group single response variable design is proposed. It involves the classification of experimental units to populations represented by the two groups. Three real data sets are provided to illustrate the utility of the classification analysis. A table of sample sizes required for the analysis is presented.…

To determine the effect of violating the assumption of homogeneity of covariance for the Tukey Wholly Significant Difference (WSD) test, Monte Carlo simulations varied the number of treatment groups, sample size, and degree of covariance heterogeneity. As covariance heterogeneity was increased, the empirical significance levels increased beyond…

This paper reviews the distinctions between classical and partial eta square and derives a formula for use in those complex analysis of variance designs in which the investigator desires a measure of classical eta square and has access only to the F-tests and relevant degrees of freedom. (Author/BW)

While tables and formulas for Fisher's z transformations are commonly included in introductory statistics books, the reverse of this transformation, namely, Fisher's z to r, is not included. Two Fisher's z to r formulas are presented. (Author)

When comparing k normal populations an investigator might want to know the probability that the population with the largest population mean will have the largest sample mean. This paper describes and illustrates methods of approximating this probability when the variances are unknown and possibly unequal. (Author/BW)

Theta is a statistic which measures the degree to which a designated pattern successfully partitions a matrix of pre- and post-treatment ratings into regions typical of each of two treatments. In this paper, theta is extended to multivariate and multigroup cases. (Author/BW)

The equivalence of one-way multivariate analysis of variance and canonical correlation is well known. The usefulness of canonical correlation analysis is performing factorial multivariate analysis of variance is demonstrated. (Author)

Sampling experiments were used to assess the Type I error rates of the t test in situations where classes were randomly assigned to groups but analyses were carried out on individual student scores. Even small amounts of between-class variation caused large inflations in the Type I error rate of the t test. (Author/BW)

A general method for identifying the separate components of the Rod-and-Frame Test consists of correlating theoretical patterns of scores with obtained test scores of single subjects. The correlation test calculates probability values from the test data. In this way, fit can be determined between theoretical pattern and test scores. (Author/BW)

This paper reports the development and standardization of the Moral Development Scale (MDS), an individually-administered set of tasks designed to assess the overall level of moral reasoning within a Piagetian framework. Data are presented on the scale's reliability and validity as well as norms derived from the cross-validation sample. (Author/BW)

A general analysis strategy is proposed such that the universe of inference is increased incrementally. The strategy prevents logically incongruent findings that occasionally result when the conventional analysis strategy is employed. (Author)

This paper demonstrates that gain score analysis and analysis of covariance (ANCOVA) will always yield conflicting results unless the slopes of within-group regression lines of posttest on pretest equal one. In Lord's specific hypothetical example, trait instability invalidates the ANCOVA. An analysis that corrects for this problem is…

A direct proof of Tucker, Cooper, and Meredith's procedure for obtaining the squared multiple correlations from a singular correlation matrix is given. (Author)

This paper explains how a major statistical package (BMDP) can be used to produce partial, semipartial, or bipartial set correlation in terms of a procedure outlined by Karpman (1980). (BW)

When homogeneity of slopes is not present, the Johnson-Neyman technique has been considered as an alternative to analysis of covariance. This paper describes how to apply the Johnson-Neyman technique for one or two covariates using the Statistical Package for the Social Sciences (SPSS) or BMDP (Biomedical Computer Programs). (Author/BW)