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Roesch, Scott C.; Aldridge, Arianna A.; Stocking, Stephanie N.; Villodas, Feion; Leung, Queenie; Bartley, Carrie E.; Black, Lisa J. – Multivariate Behavioral Research, 2010
This study used multilevel modeling of daily diary data to model within-person (state) and between-person (trait) components of coping variables. This application included the introduction of multilevel factor analysis (MFA) and a comparison of the predictive ability of these trait/state factors. Daily diary data were collected on a large (n =…
Descriptors: Structural Equation Models, Coping, Factor Analysis, Correlation
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Shieh, Gwowen – Multivariate Behavioral Research, 2009
In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…
Descriptors: Social Science Research, Sample Size, Monte Carlo Methods, Validity
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Thorndike, Robert M.; Weiss, David J. – Multivariate Behavioral Research, 1983
Three potential applications of stepwise procedures in canonical analysis and several alternative stepping decision rules are described. Results of an empirical investigation of the procedures indicated that more parsimonious approaches to maintaining variables held up better under cross-validation. (Author/JKS)
Descriptors: Correlation, Data Analysis, Multivariate Analysis, Regression (Statistics)
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Thorndike, Robert M. – Multivariate Behavioral Research, 1976
In their Monte Carlo study of canonical analysis, Barcikowski and Stevens evaluated the relative stability of canonical weights and loadings. This paper identifies some weaknesses in their study, suggests directions for future research in this area, and discusses interpretation of canonical analysis both in development and in cross-validation. For…
Descriptors: Correlation, Measurement Techniques, Monte Carlo Methods, Multivariate Analysis
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Barcikowski, Robert S.; Stevens, James P. – Multivariate Behavioral Research, 1976
This article is a rejoinder to TM 502 249. Each of Thorndike's comments are examined. A possible solution to the large number of subjects necessary for stable weights and variate-variable correlations using ridge regression procedures is suggested. (RC)
Descriptors: Correlation, Measurement Techniques, Monte Carlo Methods, Multivariate Analysis
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Cudeck, 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
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Hubert, Lawrence J.; Baker, Frank B. – Multivariate Behavioral Research, 1978
The strategy for investigating convergent and discriminant test validity, known as the multitrait-multimethod matrix, is investigated. A nonparametric significance testing procedure is suggested and demonstrated. (JKS)
Descriptors: Correlation, Hypothesis Testing, Mathematical Models, Matrices
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Harris, Richard J. – Multivariate Behavioral Research, 1976
The partitioned-U procedure is outlined, a fundamental logical flaw in this procedure's avoidance of any direct test of the significance of the first discriminant function or largest coefficient of canonical correlation is pointed out, and two alternatives to the partitioned-U procedure are discussed. (Author/DEP)
Descriptors: Analysis of Variance, Correlation, Hypothesis Testing, Multivariate Analysis
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Pavur, Robert; Nath, Ravinder – Multivariate Behavioral Research, 1984
Several general correlation patterns are shown which give exact F tests in an analysis of variance (ANOVA) procedure. They are the most general correlation patterns one can assume in a one-way and two-way layout and still have the F tests be valid. (Author/BW)
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Data Interpretation
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Delaney, Harold D.; Maxwell, Scott E. – Multivariate Behavioral Research, 1981
The use of analysis of covariance in conjunction with the multivariate approach to analyzing repeated measures designs is considered for designs involving between- and within-subject factors, one dependent variable, and one observation per subject on the covariate. (Author/RL)
Descriptors: Analysis of Covariance, Correlation, Mathematical Models, Measurement Techniques
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Frederiksen, Norman – Multivariate Behavioral Research, 1986
A procedure is suggested for test development and construct validation based on a theory about the criterion performance. The method is illustrated by describing a study concerned with the selection of medical school students, where the criterion is a measure of clinical problem-solving ability. (Author/LMO)
Descriptors: Correlation, Criterion Referenced Tests, Higher Education, Measurement Objectives
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Graham, John W.; Collins, Nancy L. – Multivariate Behavioral Research, 1991
Common approaches to examining the relationship between multitrait-multimethod (MTMM) data and variables outside the MTMM data are compared: averaging various means of each trait and estimating LISREL computer program models, and estimating only relationships between MTMM traits and the outside variables. Problems of correlational bias are…
Descriptors: Comparative Analysis, Computer Simulation, Correlation, Equations (Mathematics)
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Marsh, Herbert W. – Multivariate Behavioral Research, 1987
Masculinity and femininity were related to multiple dimensions of self-concept in responses from 962 high school students. It was found that masculinity and femininity each contributed positively and uniquely to the prediction of well-differentiated facets of self-concept. (Author/LMO)
Descriptors: Analysis of Variance, Androgyny, Construct Validity, Correlation