The use of multiple comparisons in analysis of variance (ANOVA) is discussed. It is argued that experimentwise Type I error rate inflation can be serious and that its influences are often unnoticed in ANOVA applications. Both classical balanced omnibus and orthogonal planned contrast tests inflate experimentwise error to an identifiable maximum.…

The rationale behind analysis of variance (including analysis of covariance and multiple analyses of variance and covariance) methods is reviewed, and unplanned and planned methods of evaluating differences between means are briefly described. Two advantages of using planned or a priori tests over unplanned or post hoc tests are presented. In…

Statistics used to estimate the population correlation ratio were reviewed and evaluated. The sampling distributions of Kelly's and Hays' statistics were studied empirically by computer simulation within the context of a three level one-way fixed effects analysis of variance design. (Author/RC)

The Type I error and power properties of the 2x2x2 analysis of variance (ANOVA) and tests developed by McSweeney (1967), Bradley (1979), Harwell-Serlin (1989; Harwell, 1991), and Blair-Sawilowsky (1990) were compared using Monte Carlo methods. The ANOVA was superior under the Gaussian and uniform distributions. The Blair-Sawilowsky test was…

Believing that examinee-by-item interaction should be conceptualized as true score variability rather than as a result of errors of measurement, Lu proposed a modification of Hoyt's analysis of variance reliability procedure. Via a computer simulation study, it is shown that Lu's approach does not separate interaction from error. (Author/RL)

Type I error rates of four multivariate tests (Pilai-Bartlett trace, Johansen's test, James' first-order test, and James' second-order test) were compared for heterogeneous covariance matrices in 360 simulated experiments. The superior performance of Johansen's test and James' second-order test is discussed. (SLD)

The ability of 3-way INDSCAL and ALSCAL models to recover true structure in proximity data based on 2-dimensional configurations varying in number of subjects (15 and 20) and stimuli, amount of error, and monotonic transformation is examined. INDSCAL outperformed metric and nonmetric ALSCAL in all conditions. (SLD)

Eight different methods are reviewed for determining whether two or more tests are equivalent measures. These methods vary in restrictiveness from the Wilks-Votaw test of compound symmetry (which requires that all means, variances, and covariances are equal), to Joreskog's theory of congeneric tests (which requires only that the tests are measures…

Failure to consider errors of measurement when using partial correlation or analysis of covariance techniques can result in erroneous conclusions. Certain aspects of this problem are discussed and particular attention is given to issues raised in a recent article by Brewar, Campbell, and Crano. (Author)

This study investigated seven methods for analyzing multivariate group differences. Bonferroni t statistics, multivariate analysis of variance (MANOVA) followed by analysis of variance (ANOVA), and five other methods were studied using Monte Carlo methods. Methods were compared with respect to (1) experimentwise error rate; (2) power; (3) number…

The statistical properties of two methods of estimating gain scores for groups in quasi-experiments are compared: (1) gains in scores standardized separately for each group; and (2) analysis of covariance with estimated true pretest scores. The fan spread hypothesis is assumed for groups but not necessarily assumed for members of the groups.…