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Halperin, Silas – 1976
Although analysis of variance is the most popular statistical tool to researchers in the behavioral sciences, the casual user has recognized only recently that there is no single correct way to perform such an analysis. This paper is concerned with hypotheses tested in the two-way, fixed model under a variety of conditions: (1) with and without…
Descriptors: Analysis of Variance, Comparative Analysis, Computer Programs, Hypothesis Testing
Peer reviewedHuberty, Carl J.; Wisenbaker, Joseph M. – Journal of Educational Statistics, 1992
Interpretations of relative variable importance in multivariate analysis of variance are discussed, with attention to (1) latent construct definition; (2) linear discriminant function scores; and (3) grouping variable effects. Two numerical ranking methods are proposed and compared by the bootstrap approach using two real data sets. (SLD)
Descriptors: Analysis of Variance, Comparative Analysis, Equations (Mathematics), Mathematical Models
Peer reviewedRaju, Nambury S. – Educational and Psychological Measurement, 1977
A rederivation of Lord's formula for estimating variance in multiple matrix sampling is presented as well as the ways Cronbach's coefficient alpha and the Spearman-Brown prophecy formula are related in this context. (Author/JKS)
Descriptors: Analysis of Variance, Comparative Analysis, Item Sampling, Mathematical Models
Huynh, Huynh – 1977
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…
Descriptors: Analysis of Variance, Comparative Analysis, Mathematical Models, Monte Carlo Methods
Peer reviewedMarsh, Herbert W.; Hocevar, Dennis – Journal of Educational Measurement, 1983
This paper describes a variety of confirmatory factor analysis models that provide improved tests of multitrait-multimethod matrices, and compares three different approaches (the original Campbell-Fiske guidelines, an analysis of variance model, and confirmatory factor analysis models). (PN)
Descriptors: Analysis of Variance, Comparative Analysis, Evaluation Methods, Factor Analysis
Peer reviewedLevy, Kenneth J. – Journal of Experimental Education, 1979
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)
Descriptors: Analysis of Variance, Comparative Analysis, Mathematical Models, Nonparametric Statistics
Peer reviewedChakraborti, S.; Gibbons, Jean D. – Journal of Experimental Education, 1992
The one-sided problem of comparing treatments with a standard on the basis of data available in the context of a one-way analysis of variance is examined, and the methodology of S. Chakraborti and J. D. Gibbons (1991) is extended to the case of unequal sample sizes. (SLD)
Descriptors: Analysis of Variance, Comparative Analysis, Equations (Mathematics), Mathematical Models
Krishnaiah, P. R. – 1977
Some aspects of simultaneous tests for means are reviewed. Specifically, the comparison of univariate or multivariate normal populations based on the values of the means or mean vectors when the variances or covariance matrices are equal is discussed. Tukey's and Dunnett's tests for multiple comparisons of means, Scheffe's method of examining…
Descriptors: Analysis of Variance, Comparative Analysis, Data Analysis, Hypothesis Testing
Peer reviewedBintig, Arnfried – Educational and Psychological Measurement, 1980
Twelve variance-analytical and nonparametrical coefficients of reliability for rating scales designed for rating persons were compared to each other theoretically and empirically. Preference for two coefficients was established. The intraclass correlation coefficient appeared to be useful for the estimation of reliability as well. (Author/RL)
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Mathematical Models
Peer reviewedHarwell, Michael R. – Educational Research Quarterly, 1988
Multivariate and univariate analysis of variance methods (MANOVA and ANOVA, respectively) are compared for their relative value in educational research. The favoritism shown multivariate techniques is questioned. Criteria for the selection of the appropriate technique are outlined. The relationships among research hypotheses, statistical…
Descriptors: Analysis of Variance, Comparative Analysis, Educational Research, Hypothesis Testing
Peer reviewedWerts, Charles E.; Linn, Robert L. – Educational and Psychological Measurement, 1971
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Mathematical Models
Hsiung, Tung-Hsing; Olejnik, Stephen – 1993
This study considers the problem of performing all pairwise comparisons of column means for a two-by-four additive nonorthogonal factorial analysis of variance (ANOVA) model where cell variances are heterogeneous. Extensions of the following procedures are considered: (1) Games-Howell (1976) procedure; (2) the C. W. Dunnett (1980) T3 and C…
Descriptors: Analysis of Variance, Comparative Analysis, Computer Simulation, Equations (Mathematics)
Peer reviewedBlair, R. Clifford; Higgins, J. J. – Florida Journal of Educational Research, 1984
R. V. Hopkins (1982) has criticized the use of means as the unit of analysis in situations where intact groups, such as classes, rather than individuals have been randomly assigned to various treatment conditions. Instead, Hopkins advocated the use of certain analysis of variance (ANOVA) models that, as far as test for treatment effects are…
Descriptors: Analysis of Variance, Classrooms, Comparative Analysis, Elementary Secondary Education
Peer reviewedLevin, Joel R. – Journal of Educational Measurement, 1975
A set procedure developed in this study is useful in determining sample size, based on specification of linear contrasts involving certain formula treatments. (Author/DEP)
Descriptors: Analysis of Variance, Comparative Analysis, Mathematical Models, Measurement Techniques
Dalton, Starrette – 1976
The degree of nonorthogonality in a factorial design was systematically increased. Five methods of dealing with nonorthogonality were selected and applied: two were least squares solutions (Method 1 and Method 2); two were approximate solutions (the unweighted means analysis and the method of expected frequencies); and the fifth was the…
Descriptors: Analysis of Variance, Comparative Analysis, Data Analysis, Least Squares Statistics


