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| Psychometrika | 8 |
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Peer reviewedMulaik, Stanley A. – Psychometrika, 1976
Discusses Guttman's index of indeterminacy in light of alternative solutions which are equally likely to be correct and alternative solutions for the factor which are not equally likely to be chosen. Offers index which measures a different aspect of the same indeterminacy problem. (ROF)
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices
Peer reviewedGreen, Bert F. Jr. – Psychometrika, 1976
A summary and interpretation of the recent literature on the indeterminancy of factor scores is given in simple terms. A good index of factor score determinancy is the squared multiple correlation of the factor with the observed variables. (Author)
Descriptors: Correlation, Factor Analysis, Factor Structure, Multiple Regression Analysis
Peer reviewedSchonemann, Peter H.; Wang, Ming-Mei – Psychometrika, 1972
Relations between maximum likelihood factor analysis and factor indeterminacy are discussed. (CK)
Descriptors: Algorithms, Correlation, Factor Analysis, Factor Structure
Lorenzo-Seva, Urbano; Rodriguez-Fornells, Antoni – Psychometrika, 2006
Personality tests often consist of a set of dichotomous or Likert items. These response formats are known to be susceptible to an agreeing-response bias called acquiescence. The common assumption in balanced scales is that the sum of appropriately reversed responses should be reasonably free of acquiescence. However, inter-item correlation (or…
Descriptors: Factor Analysis, Correlation, Factor Structure, Personality Measures
Peer reviewedKorth, Bruce; Tucker, Ledyard R. – Psychometrika, 1975
Provides normative data about the distribution of one measure of similarity of factor loadings, the congruence coefficient, through a Monte Carlo Technique. Matching of "chance" factor patterns was done by the method of Tucker. Statistical tests of the results, based on similarities of the method to canonical and multiple correlation,…
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices
Peer reviewedMcDonald, Roderick P. – Psychometrika, 1978
The relationship between the factor structure of a convariance matrix and the factor structure of a partial convariance matrix when one or more variables are partialled out of the original matrix is given in this brief note. (JKS)
Descriptors: Analysis of Covariance, Correlation, Factor Analysis, Factor Structure
Peer reviewedHakstian, A. Ralph – Psychometrika, 1971
The oblimax, promax, maxplane, and Harris-Kaiser techniques are compared. (Author)
Descriptors: Comparative Analysis, Correlation, Factor Analysis, Factor Structure
Peer reviewedChristoffersson, Anders – Psychometrika, 1975
An approach for multiple factor analysis of dichotomized variables is presented based on distribution of first and second order joint probabilities of binary scored items. The estimator is based on the generalized least squares principle. Standard errors and a test of the fit of the model is given. (Author/RC)
Descriptors: Analysis of Covariance, Computer Programs, Correlation, Factor Analysis

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