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Betz, M. Austin; Elliott, Steven D. – Journal of Educational Statistics, 1984
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.…
Descriptors: Analysis of Variance, Estimation (Mathematics), Hypothesis Testing, Multivariate Analysis
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Haertel, Edward H.; Thoresen, Carl E. – Counseling Psychologist, 1987
Comments on Kerwin et al.'s article on Covariance Structure analysis (LISREL). Concerns include assumptions about requirements for causal inferences, psychometric properties of measurement scales, validity of the indicators of each latent variable, completeness of the structural model, linearity of the latent variables, and the joint distribution…
Descriptors: Computer Software, Cost Effectiveness, Counseling, Multivariate Analysis
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Games, Paul A.; Hedges, Larry V. – Journal of Experimental Education, 1987
Variance stabilizing transformations yield statistics whose standard errors are only influenced by the number of observations on which they are based. A solution that can be extended to inference on all of these parameters is presented and illustrated via three examples. (TJH)
Descriptors: Correlation, Error of Measurement, Least Squares Statistics, Multivariate Analysis
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Sclove, Stanley L. – Psychometrika, 1987
A review of model-selection criteria is presented, suggesting their similarities. Some problems treated by hypothesis tests may be more expeditiously treated by the application of model-selection criteria. Multivariate analysis, cluster analysis, and factor analysis are considered. (Author/GDC)
Descriptors: Cluster Analysis, Evaluation Criteria, Factor Analysis, Hypothesis Testing
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Boodoo, Gwyneth M. – Journal of Special Education, 1985
A multivariate model is proposed for assessing a severe discrepancy between intellectual ability and actual achievement in learning disabled (LD) children. Formulas for computing universe difference score variance, the standard error of the difference score, and its generalizability coefficient are given. (Author)
Descriptors: Academic Achievement, Aptitude, Disability Identification, Elementary Secondary Education
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Huberty, Carl J. – Educational and Psychological Measurement, 1983
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)
Descriptors: Analysis of Variance, Correlation, Data Analysis, Hypothesis Testing
Witta, E. Lea – 2000
Because ignoring the missing data in an evaluation may lead to results that are questionable, this study investigated the effects of use of four missing data handling techniques on a survey instrument. A questionnaire containing 35 5-point Likert-style questions was completed by 384 respondents. Of these, 166 (43%) questionnaires contained 1 or…
Descriptors: Evaluation Methods, Factor Analysis, Factor Structure, Likert Scales
Ainsworth, Martha; Beegle, Kathleen; Koda, Godlike – 2002
The AIDS epidemic is making orphans out of many African children and threatens to reverse hard-won gains in raising school enrollments. The average gross primary enrollment ration (GPER) the number of children enrolled as a percent of the total number of children of school age was only 77% for Sub-Saharan Africa in 1996. The countries are hard-hit…
Descriptors: Developing Nations, Economic Status, Educational Research, Elementary Education
Kennedy, Robert L.; McCallister, Corliss Jean – 2001
This study investigated the attitudes toward statistics of graduate students who studied advanced statistics in a course in which the focus of instruction was the use of a computer program in class. The use of the program made it possible to provide an individualized, self-paced, student-centered, and activity-based course. The three sections…
Descriptors: Computer Uses in Education, Graduate Students, Graduate Study, Higher Education
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Merenda, Peter F.; And Others – Educational and Psychological Measurement, 1972
Descriptors: Achievement Tests, Aptitude Tests, Comparative Analysis, Correlation
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Meredith, William; Tisak, John – Psychometrika, 1982
When measuring the same variables on different occasions, two procedures for canonical analysis with stationary compositing weights are developed. Both methods are extended to allow for cohort sequential designs and a numerical illustration is presented. (Author/JKS)
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Data Analysis
Peer reviewed Peer reviewed
Strahan, Robert F. – Journal of Counseling Psychology, 1982
Calls attention to limitations and dangers in routine application of multivariate analysis of variance (MANOVA), describes some alternative procedures, and laments the necessarily pervasive character of the statistical problem. (Author)
Descriptors: Analysis of Variance, Multivariate Analysis, Position Papers, Research Methodology
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Baggaley, Andrew R. – Evaluation Review, 1981
A diagram is used to aid discussion of how several of the frequently used multivariate statistical techniques are interrelated. All of those discussed can be regarded as special cases of canonical correlation. (Author)
Descriptors: Analysis of Variance, Behavioral Science Research, Discriminant Analysis, Measurement Techniques
Marx, Ronald W.; Winne, Philip H. – Measurement and Evaluation in Guidance, 1980
Two studies involving a total of 837 intermediate-grade students found that multivariate analyses of self-concept inventories reveal dimensions uncovered by univariate methods. (NRB)
Descriptors: Children, Data Analysis, Intermediate Grades, Multivariate Analysis
Mihevic, Patricia M.; Spray, Judith A. – Research Quarterly, 1979
A multivariate post hoc procedure (the Roy-Bose procedure) which allows for the construction of an infinite number of confidence intervals or probability statements concerning the p variables, all of which hold at a 100(1-a) percent level of confidence, is demonstrated and compared to other procedures. (JD)
Descriptors: Analysis of Variance, Comparative Analysis, Exercise Physiology, Factor Analysis
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