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Showing 1 to 15 of 28 results Save | Export
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Gignac, Gilles E.; Watkins, Marley W. – Multivariate Behavioral Research, 2013
Previous confirmatory factor analytic research that has examined the factor structure of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) has endorsed either higher order models or oblique factor models that tend to amalgamate both general factor and index factor sources of systematic variance. An alternative model that has not yet…
Descriptors: Intelligence Tests, Test Reliability, Factor Structure, Models
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Woods, Carol M. – Multivariate Behavioral Research, 2008
Person fit is the degree to which an item response model fits for individual examinees. Reise (2000) described how two-level logistic regression can be used to detect heterogeneity in person fit, evaluate potential predictors of person fit heterogeneity, and identify potentially aberrant individuals. The method has apparently never been applied to…
Descriptors: Simulation, Test Reliability, Measures (Individuals), Item Response Theory
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Joe, George W.; Woodward, J. Arthur – Multivariate Behavioral Research, 1975
Descriptors: Correlation, Matrices, Sampling, Statistical Analysis
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Krishnamoorthy, K.; Xia, Yanping – Multivariate Behavioral Research, 2006
The conventional approach for testing the equality of two normal mean vectors is to test first the equality of covariance matrices, and if the equality assumption is tenable, then use the two-sample Hotelling T[superscript 2] test. Otherwise one can use one of the approximate tests for the multivariate Behrens-Fisher problem. In this article, we…
Descriptors: Statistical Analysis, Test Reliability, Test Selection, Error Patterns
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Silverstein, A. B.; Fisher, Gary – Multivariate Behavioral Research, 1975
Responses of male prisoners to the Personal Orientation Inventory were clustered, using hierarchical linkage analysis. Six second-order clusters accounted for all the items. Reliabilities of these clusters were comparable to those of the first-order clusters. Relative validity of cluster scores and scale scores remains to be determined. (RC)
Descriptors: Cluster Analysis, Correlation, Item Analysis, Personality Measures
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Nesselroade, John R.; Cable, Dana G. – Multivariate Behavioral Research, 1974
Using the personality trait versus state distinction as a substantive context, the fit of the factor analytic model to difference score data is investigated and found to be quite good. Methodological issues related to properties of difference scores and their implications for personality research are briefly discussed. (Author)
Descriptors: Anxiety, Factor Analysis, Measurement Techniques, Personality
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Paunonen, Sampo V. – Multivariate Behavioral Research, 1987
Study determines that solutions derived by multiple group analysis and item-total correlation analysis were generally most interpretable from a psychological perspective. It was concluded that their application to test construction is preferred over Procrustean or confirmatory maximum likelihood approaches. (RB)
Descriptors: Correlation, Data Analysis, Factor Analysis, Psychological Testing
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O'Grady, Kevin E. – Multivariate Behavioral Research, 1988
Various psychometric characteristics of the Marlowe-Crowne and Edwards Social Desirability scales were assessed in a sample of 108 male and 189 female undergraduates. Results suggest that males and females show different means and similar internal consistency reliability and intercorrelation on the two scales. (TJH)
Descriptors: Measures (Individuals), Psychometrics, Sex Differences, Social Desirability
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Lee, Kibeom; Ashton, Michael C. – Multivariate Behavioral Research, 2004
We introduce a personality inventory designed to measure six major dimensions of personality derived from lexical studies of personality structure. The HEXACO Personality Inventory (HEXACO-PI) consists of 24 facet-level personality trait scales that define the six personality factors named Honesty-Humility (H), Emotionality (E), Extraversion (X),…
Descriptors: Psychometrics, Personality Measures, Personality Assessment, Personality Traits
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Wolfe, John H. – Multivariate Behavioral Research, 1978
Published data on the Strong Vocational Interest Blank profiles of 113 occupational groups are analyzed by three clustering procedures: hierachical grouping of standard scores and of orthonormal factor scores, and NORMIX analysis assuming equal covariance matrices for each group. (Author/JKS)
Descriptors: Cluster Analysis, Interest Inventories, Occupational Tests, Occupations
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Hsu, Louis M. – Multivariate Behavioral Research, 1992
D.V. Budescu and J.L. Rogers (1981) proposed a method of adjusting correlations of scales to eliminate spurious components resulting from the overlapping of scales. Three reliability correction formulas are derived in this article that are based on more tenable assumptions. (SLD)
Descriptors: Correlation, Equations (Mathematics), Mathematical Models, Personality Measures
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Silverstein, A. B.; Fisher, Gary – Multivariate Behavioral Research, 1974
Descriptors: Cluster Analysis, Factor Analysis, Factor Structure, Males
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Conger, Anthony J. – Multivariate Behavioral Research, 1974
Two indices of profile reliability are shown to be equivalent in terms of the individual independent canonical composites; however, because of different weighting procedures, they yield different overall indices of profile reliability. A common formula is provided from which both indices can be derived. (Author)
Descriptors: Analysis of Variance, Correlation, Matrices, Measurement Techniques
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Payne, Frank D. – Multivariate Behavioral Research, 1974
Descriptors: Ambiguity, Personality Assessment, Personality Measures, Response Style (Tests)
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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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