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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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Huang, Po-Hsien; Weng, Li-Jen – Multivariate Behavioral Research, 2012
A procedure for estimating the reliability of test scores in the context of ecological momentary assessment (EMA) was proposed to take into account the characteristics of EMA measures. Two commonly used test scores in EMA were considered: the aggregated score (AGGS) and the within-person centered score (WPCS). Conceptually, AGGS and WPCS represent…
Descriptors: Reliability, Scores, Correlation, Computation
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Raykov, Tenko – Multivariate Behavioral Research, 2000
Outlines a correlation structures modeling approach to the study of stability in reliability of multiple, repeatedly administered measures and illustrates the method on data from a fluid intelligence study (P. Bates and others, 1986). The method is also applicable when examining relationships between model parameters across all variables.…
Descriptors: Correlation, Models, Reliability
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Joe, George W.; Woodward, J. Arthur – Multivariate Behavioral Research, 1975
Descriptors: Correlation, Matrices, Sampling, Statistical Analysis
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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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Barcikowski, Robert S.; Stevens, James P. – Multivariate Behavioral Research, 1975
Results showed that the canonical correlations are very stable upon replication. The results also indicated that there is no solid evidence for concluding that components are superior to the coefficients, at least not in terms of being more reliable. (Author/BJG)
Descriptors: Correlation, Factor Analysis, Matrices, Monte Carlo Methods
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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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Huberty, Carl J.; And Others – Multivariate Behavioral Research, 1986
Three methods of transforming unordered categorical response variables are described: (1) analysis using dummy variables; (2) eigenanalysis of frequency patterns scaled relative to within-groups variance; (3) categorical variables analyzed separately with scale values generated so that the grouping variable and the categorical variable are…
Descriptors: Classification, Correlation, Discriminant Analysis, Measurement Techniques
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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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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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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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Dudzinski, M. L.; And Others – Multivariate Behavioral Research, 1975
Descriptors: Comparative Analysis, Correlation, Factor Analysis, Homogeneous Grouping
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Bernstein, Ira H.; And Others – Multivariate Behavioral Research, 1986
A three subscale inventory designed by Fenigstein, Scheier, and Buss to measure self-consciousness was administered to 297 college students. Fenigstein et al.'s representation was found to fit the data in its original form. Items on the subscales differ nearly as much statistically as they do substantively. (Author/LMO)
Descriptors: College Students, Correlation, Factor Analysis, Factor Structure