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Direct linkHafdahl, Adam R. – Journal of Educational and Behavioral Statistics, 2007
The originally proposed multivariate meta-analysis approach for correlation matrices--analyze Pearson correlations, with each study's observed correlations replacing their population counterparts in its conditional-covariance matrix--performs poorly. Two refinements are considered: Analyze Fisher Z-transformed correlations, and substitute better…
Descriptors: Monte Carlo Methods, Correlation, Meta Analysis, Matrices
Peer reviewedBarcikowski, Robert S.; Stevens, James P. – Multivariate Behavioral Research, 1975
Results showed that the canonical correlations are very stable upon replication. The results also indicated that there is no solid evidence for concluding that components are superior to the coefficients, at least not in terms of being more reliable. (Author/BJG)
Descriptors: Correlation, Factor Analysis, Matrices, Monte Carlo Methods
Peer reviewedReddon, John R.; And Others – Journal of Educational Statistics, 1985
Computer sampling from a multivariate normal spherical population was used to evaluate the type one error rates for a test of sphericity based on the distribution of the determinant of the sample correlation matrix. (Author/LMO)
Descriptors: Computer Simulation, Correlation, Error of Measurement, Matrices
Peer reviewedThompson, Bruce – Journal of Experimental Education, 1991
Monte Carlo methods were used to evaluate the degree to which canonical function and structure coefficients may be differentially sensitive to sampling error. For each of 64 research situations, 1,000 random samples were drawn. Both sets of coefficients were roughly equally influenced; some exceptions are noted. (SLD)
Descriptors: Behavioral Science Research, Computer Simulation, Correlation, Matrices
Peer reviewedSpiegel, Douglas K. – Multivariate Behavioral Research, 1986
Tau, Lambda, and Kappa are measures developed for the analysis of discrete multivariate data of the type represented by stimulus response confusion matrices. The accuracy with which they may be estimated from small sample confusion matrices is investigated by Monte Carlo methods. (Author/LMO)
Descriptors: Mathematical Models, Matrices, Monte Carlo Methods, Multivariate Analysis
Peer reviewedFouladi, Rachel T.; Steiger, James H. – Educational and Psychological Measurement, 1993
The test proposed by Brien, Venables, and Mayo (1984), endorsed by Silver and Dunlap, and supported by computer software that they developed is not a proper test for multivariate independence. A revised appraisal is suggested for the Silver and Dunlap results. (SLD)
Descriptors: Computer Software, Computer Software Development, Correlation, Matrices
Download full textBeasley, T. Mark; Sheehan, Janet K. – 1994
C. L. Olson (1976, 1979) suggests the Pillai-Bartlett trace (V) as an omnibus multivariate analysis of variance (MANOVA) test statistic for its superior robustness to heterogeneous variances. J. Stevens (1979, 1980) contends that the robustness of V, Wilk's lambda (W) and the Hotelling-Lawley trace (T) are similar, and that their power functions…
Descriptors: Analysis of Covariance, Comparative Analysis, Matrices, Monte Carlo Methods
