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Marcoulides, George A. – Educational and Psychological Measurement, 1994
Effects of different weighting schemes on selecting the optimal number of observations in multivariate-multifacet generalizability designs are studied when cost constraints are imposed. Comparison of four schemes through simulation indicates that all four produce similar optimal values and that reliability should be similar. (SLD)
Descriptors: Budgeting, Comparative Analysis, Costs, Factor Analysis
Peer reviewed Peer reviewed
Keselman, H. J. – Journal of Educational Statistics, 1994
Six stepwise multiple-comparison procedures for repeated-measures means were compared for their overall familywise rates of Type I error when multisample sphericity and multivariate normality were not satisfied. Robust stepwise procedures were identified by Keselman, Keselman, and Shaffer (1991) with respect to three definitions of power. (SLD)
Descriptors: Comparative Analysis, Equations (Mathematics), Monte Carlo Methods, Multivariate Analysis
Chastain, Robert L.; Joe, George W. – 1986
Multivariate methods were used to identify between-set factors relating the criterion set of eleven Wechsler Adult Intelligence Scale Revised subtest variables to the predictor set of demographic variables: age, race, sex, education, occupation, geographic region, and urban versus rural residence. Although factor analysis is usually used to…
Descriptors: Adults, Comparative Analysis, Correlation, Factor Analysis
Beasley, 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
Thompson, Bruce – 1985
Hypothetical data sets are used to demonstrate how canonical correlation methods subsume other commonly utilized parametric methods. Analysis of variance, analysis of covariance, multiple analysis of variance, and multiple analysis of covariance are heavily used by educational researchers. It is concluded that researchers would do well to consider…
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Correlation
Peer reviewed Peer reviewed
Tang, K. Linda; Algina, James – Multivariate Behavioral Research, 1993
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)
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Equations (Mathematics)
Robey, Randall R.; Barcikowski, Robert S. – 1986
This paper reports the results of a Monte Carlo investigation of Type I errors in the single group repeated measures design where multiple measures are collected from each observational unit at each measurement occasion. The Type I error of three multivariate tests were examined. These were the doubly multivariate F test, the multivariate mixed…
Descriptors: Analysis of Variance, Behavioral Science Research, Comparative Analysis, Hypothesis Testing
Hummel, Thomas J.; Johnston, Charles B. – 1986
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…
Descriptors: Analysis of Variance, Comparative Analysis, Correlation, Differences