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Peer reviewedHuck, Schuyler W.; Layne, Benjamin H. – Educational and Psychological Measurement, 1974
Descriptors: Analysis of Variance, Matrices, Statistical Analysis
Peer reviewedCoombs, William T.; Algina, James – Educational and Psychological Measurement, 1996
Univariate procedures proposed by M. Brown and A. Forsythe (1974) and the multivariate procedures from D. Nel and C. van der Merwe (1986) were generalized to form five new multivariate alternatives to one-way multivariate analysis of variance (MANOVA) for use when dispersion matrices are heteroscedastic. These alternatives are evaluated for Type I…
Descriptors: Analysis of Variance, Matrices, Multivariate Analysis
Woodruff, David J. – 1995
The one observation per cell two-way items by examinees random effects analysis of variance (ANOVA) with all error components zero is considered. The estimated variance components are expressed as functions of the inter-item covariance matrix and the inter-examinee covariance matrix. These expressions show that under the random effects model if…
Descriptors: Analysis of Variance, Estimation (Mathematics), Matrices, Test Items
Woodruff, David J. – 1995
The one observation per cell two-way items by examinees random effects analysis of variance (ANOVA) with all error components zero is considered. The estimated variance components are expressed as functions of the inter-item covariance matrix and the inter-examinee covariance matrix. These expressions show that under the random effects model if…
Descriptors: Analysis of Variance, Estimation (Mathematics), Matrices, Test Items
Peer reviewedKrus, David J.; Wilkinson, Sue Marie – Educational and Psychological Measurement, 1986
Matrix differencing of data vectors is introduced as a method for computing test variance and is compared to traditional analysis of variance. Applications for computer assisted instruction, provided by supplemental computer software, are also described. (Author/GDC)
Descriptors: Analysis of Variance, Comparative Analysis, Computer Software, Matrices
Peer reviewedWallenstein, Sylvan; Fleiss, Joseph L. – Psychometrika, 1979
The multiplicative correction term for the degrees of freedom in a repeated measures analysis of variance table is given for the cases in which there is equal variability per time point, and the correlation between observations is k time units apart. This correction equals the correlation coefficient raised to the kth power. (JKS)
Descriptors: Analysis of Variance, Correlation, Hypothesis Testing, Matrices
Peer reviewedKaufman, David; Sweet, Robert – American Educational Research Journal, 1974
The use of multiple regression as a data-analytic tool is examined for the cases of balanced and unbalanced designs. The utility of this method for testing specific contrasts, both orthogonal and nonorthogonal is discussed and some interpretive cautions are examined. (Author)
Descriptors: Analysis of Variance, Codification, Matrices, Multiple Regression Analysis
Dziuban, Charles D.; And Others – 1976
The distributional characteristics of the Kaiser-Rice measure of sampling adequacy (MSA) were investigated with sample correlation matrices from multivariate normal populations where the level of correlation (LC) was systematically varied. Two additional variables were manipulated--sample size (SS) and number of variables (NV). Ten matrices were…
Descriptors: Analysis of Variance, Correlation, Factor Analysis, Matrices
Draper, John F. – 1974
A study was made of the problem of representing the expectations of mean squares associated with analysis of variance sources of variation for experimental designs. These designs have a factorial structure over repeated measures or, for some other reason, have variates within a factorial design not all of which are mutually independent. A simple…
Descriptors: Analysis of Variance, Expectation, Hypothesis Testing, Mathematical Models
Peer reviewedVelicer, Wayne F.; Fava, Joseph L. – Multivariate Behavioral Research, 1987
Principal component analysis, image component analysis, and maximum likelihood factor analysis were compared to assess the effects of variable sampling. Results with respect to degree of saturation and average number of variables per factor were clear and dramatic. Differential effects on boundary cases and nonconvergence problems were also found.…
Descriptors: Analysis of Variance, Factor Analysis, Mathematical Models, Matrices
Peer reviewedDreger, Ralph Mason – Educational and Psychological Measurement, 1979
A program is described utilizing a microcomputer and tape drive with any contingency or chi-square table from 2x2 to 8x8. It requires only the entering of the number of rows and number of columns, plus one-time entry of cell frequencies. (Author/JKS)
Descriptors: Analysis of Variance, Computer Programs, Computers, Matrices
Peer reviewedGames, Paul A. – Educational and Psychological Measurement, 1975
Describes a set of five programs providing robust techniques that work well when the assumption of conventional analysis of variance have been violated. (Author/RC)
Descriptors: Analysis of Variance, Computer Programs, Matrices, Research Design
Peer reviewedJohnson, Richard M. – Psychometrika, 1975
A simple method of monotone regression is described based on the principle of minimizing pairwise departures from monotonicity. (Author)
Descriptors: Analysis of Variance, Goodness of Fit, Matrices, Measurement Techniques
Peer reviewedBell, John F. – Journal of Educational Statistics, 1985
This paper outlines the problems associated with the estimation of variance components in generalizability analyses using analysis of variance software, and discusses the most useful software currently available for this specialist application: the MIVQUE method of the Statistical Analysis System (SAS) procedure VARCOMP. (Author)
Descriptors: Analysis of Variance, Computer Software, Generalizability Theory, Matrices
Peer reviewedJoe, George W.; Woodward, J. Arthur – Psychometrika, 1976
This article is concerned with estimation of components of maximum generalizability in multifacet experimental designs involving multiple dependent measures. An example of a two-facet partially nested design is provided. (Author/RC)
Descriptors: Analysis of Variance, Correlation, Matrices, Reliability


