This paper develops a general method for comparing treatment magnitudes for research employing multiple treatment fixed effects analysis of variance designs, which may be used for main effects with any number of levels without regard to directionality. (Author/BS)

Using computer simulation, parametric analysis of covariance (ANCOVA) was compared to ANCOVA with data transformed using ranks, in terms of proportion of Type I errors and statistical power. Results indicated that parametric ANCOVA was robust to violations of either normality or homoscedasticity, but practiced significant power differences favored…

The method of unweighted means in the multivariate analysis of variance with unequal sample sizes was investigated. By approximating the distribution of the hypothesis sums-of-squares-and-cross-products with a Wishart distribution, multivariate test statistics were derived. Monte Carlo methods and a numerical example illustrate the technique.…

The relation between the power of a significance test in a block design with correlated measurements and the reliability of the measuring instrument is analyzed in terms of the components of variance entering the reliability coefficient and the noncentrality parameter. (Author/LMO)

Attempts to distill a growing technical literature on repeated-measures analysis of variance into a few simple principles for selecting an analytic technique. Argues that researchers ought not opt for a general analysis strategy when current computer technology makes it possible to select the optimal analysis technique for a given data set. (RH)

This paper discusses the sample size problem and four factors affecting its solution: significance level, statistical power, analysis procedure, and effect size. The interrelationship between these factors is discussed and demonstrated by calculating minimal sample size requirements for a variety of research conditions. (Author)

The basic notion of variability is generalized from a univariate context to a multivariate context using two matrix functions, a determinant, and a trace, yielding a number of alternative multivariate indices of shared variation. Some problems in the interpretation of tests of multivariate hypotheses are reviewed. (Author/BW)

A Bradley-Terry type model for paired comparisons is considered which allows for individual parameters and corresponding parameters for the choice-alternatives. Model is applied to data from a Danish investigation of blue collar attitudes towards alternative social gains. Model is compared to one suggested by Schonemann and Wang. (RC)

Details of a reasonably precise normalization technique for coefficient alpha are outlined, along with methods for estimating the variance of the normalized statistic. These procedures lead to the K-sample significance test. (RC)

Many program evaluations involve some type of statistical testing to verify that the program has succeeded in accomplishing initially established goals. In many cases, this takes the form of null hypothesis significance testing (NHST) with t-tests, analysis of variance, or some form of the general linear model. This paper contends that, at least…

As an extension of B. Thompson's 1998 invited address to the American Educational Research Association, this paper cites two additional common faux pas in research methodology and explores some research issues for the future. These two errors in methodology are the use of univariate analyses in the presence of multiple outcome variables (with the…

This paper describes two statistics (chi square and Kendall's S) which may be used to test hypotheses about the association between two variables when observations are cross-classified in a contingency table. (CK)

This chapter presents several facets of a new approach that uses generalizability theory to conduct cross-level inference in psychological and educational research. Unlike past models for cross-level research, this approach facilitates multiple-level investigations to test the external validity of results and findings. (Author/PN)