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Newman, Isadore; Fraas, John W.; Newman, Carole – 2002
This paper presents a discussion of various statistical concepts and techniques in light of two propositions. The first is that researchers need to select analytical techniques that prevent them from committing Type VI errors, which are inconsistencies between the research question and the statistical analysis. The second is that many statistical…
Descriptors: Multivariate Analysis, Research Design, Research Methodology, Statistical Analysis
Peer reviewedCudeck, Robert; Browne, Michael W. – Multivariate Behavioral Research, 1983
Methods for comparing the suitability of alternative models for covariance matrices are examined. A cross-validation procedure is suggested and its properties examined. A series of examples using longitudinal data are examined. (Author/JKS)
Descriptors: Correlation, Data Analysis, Multiple Regression Analysis, Multivariate Analysis
Peer reviewedRoss, Donald C. – Educational and Psychological Measurement, 1983
Theta is a statistic which measures the degree to which a designated pattern successfully partitions a matrix of pre- and post-treatment ratings into regions typical of each of two treatments. In this paper, theta is extended to multivariate and multigroup cases. (Author/BW)
Descriptors: Hypothesis Testing, Matrices, Multivariate Analysis, Research Methodology
Peer reviewedBray, James H.; Maxwell, Scott E. – Review of Educational Research, 1982
The available methods for analyzing and interpreting data with multivariate analysis of variance are reviewed, and guidelines for their use are presented. Causal models that underlie the various methods are presented to facilitate the use and understanding of the methods. (Author/PN)
Descriptors: Analysis of Variance, Discriminant Analysis, Mathematical Models, Multivariate Analysis
Peer reviewedNussbaum, Albert – Journal of Educational Measurement, 1982
In response to Webb and Shavelson (EJ 241 567), Nussbaum questions the relevance of the universe score variance as a meaning reliability index and whether it is useful to determine the weights which enter into a composite by means of maximum generalizability. (CM)
Descriptors: Analysis of Covariance, Analysis of Variance, Cognitive Tests, Multivariate Analysis
Peer reviewedWebb, Noreen M.; Shavelson, Richard J. – Journal of Educational Measurement, 1982
Answering Nussbaum's (TM 507 069) criticism, the generalizability coefficient for absolute decisions, the use of the error variance formula, composites of maximum generalizability, and covariance components are discussed as yardsticks of measurement precision with arguments for the use of each procedure to interpret data. (CM)
Descriptors: Analysis of Covariance, Analysis of Variance, Cognitive Tests, Multivariate Analysis
Peer reviewedSzatrowski, Ted – Journal of Educational Statistics, 1982
Known results for testing and estimation problems for patterned means and covariance matrices with explicit linear maximum likelihood estimates are applied to the block compound symmetry problem. An example involving educational testing is provided. (Author/JKS)
Descriptors: Hypothesis Testing, Mathematical Models, Maximum Likelihood Statistics, Multivariate Analysis
Peer reviewedPickett, Lawrence K., Jr. – Criminal Justice and Behavior, 1981
The MMPI results obtained from 245 adolescent males referred to the evaluation unit of a Juvenile Court were submitted to a multivariate classification system. By correlating individual subject profiles with the modal profiles, six membership groups were formed. No relationship was found between group membership and age or race. (Author)
Descriptors: Adolescents, Age, Classification, Cluster Grouping
Peer reviewedHuberty, Carl J.; Smith, Jerry D. – Multivariate Behavioral Research, 1982
A particular strategy for investigating effects from a multivariate analysis of variance (MANOVA) is proposed. The strategy involves multiple two-group multivariate analyses. The analysis strategy is described in detail and illustrated with real data sets. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Multivariate Analysis, Research Design
Peer reviewedBagozzi, Richard P. – Multivariate Behavioral Research, 1981
Canonical correlation analysis is considered to be a general model for bivariate and multivariate statistical methods. Some problems involving assumptions and statistical tests for parameters exist for social science data. A resolution for these problems is presented by treating canonical correlation as a special case of linear structural…
Descriptors: Correlation, Data Analysis, Hypothesis Testing, Mathematical Models
Peer reviewedCramer, Elliot M.; Nicewander, W. Alan – Psychometrika, 1979
A distinction is drawn between redundancy measurement and the measurement of multivariate association between two sets of variables. Several measures of multivariate association between two sets of variables are examined. (Author/JKS)
Descriptors: Correlation, Measurement, Multiple Regression Analysis, Multivariate Analysis
Peer reviewedLongford, Nicholas T. – Psychometrika, 1997
It is demonstrated that, in the presence of population information, a linear combination of true scores can be estimated more efficiently than by the same linear combination of the observed scores. Three criteria for optimality are discussed, but they yield the same solution, described as a multivariate shrinkage estimator. (Author/SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Multivariate Analysis, Population Distribution
Peer reviewedBargmann, Rolf – Journal of Educational Statistics, 1989
Use of internal correlation for statistical analysis--as proposed by G. W. Joe and J. L. Mendoza (1989)--is discussed. Use of the bootstrap technique to deal with the distributional problem is questioned. Joe and Mendoza attempt the interpretation of the two linear composites that produce the largest internal correlation. (TJH)
Descriptors: Correlation, Factor Analysis, Generalization, Multivariate Analysis
Peer reviewedSchuenemeyer, John H. – Journal of Educational Statistics, 1989
The use of internal correlation for statistical analysis, as proposed by G. W. Joe and J. L. Mendoza (1989), is discussed. The suggestion of using bootstrapping is received well. Applications to collinearity are suggested. (TJH)
Descriptors: Correlation, Factor Analysis, Generalization, Multivariate Analysis
Peer reviewedHuizenga, Hilde M.; Molenaar, Peter C. M. – Multivariate Behavioral Research, 1994
The source of an event-related brain potential (ERP) is estimated from multivariate measures of ERP on the head under several mathematical and physical constraints on the parameters of the source model. Statistical aspects of estimation are discussed, and new tests are proposed. (SLD)
Descriptors: Estimation (Mathematics), Evaluation Methods, Models, Multivariate Analysis


