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Peer reviewedLee, Howard B.; Comrey, Andrew L. – Multivariate Behavioral Research, 1978
Two proposed methods of factor analyzing a correlation matrix using only the off-diagonal elements are compared. The purpose of these methods is to avoid using the diagonal communality elements which are generally unknown and must be estimated. (Author/JKS)
Descriptors: Comparative Analysis, Correlation, Factor Analysis, Matrices
Peer reviewedBolton, Brian – Rehabilitation Counseling Bulletin, 1978
A group of 31 clients completed the Human Service Scale and were evaluated by their counselors, who used the Client Outcome Measure at the time of the clients' acceptance for rehabilitation services and again at closure. Results were generally consistent with those of previous investigations. (Author)
Descriptors: Behavior Change, Counseling Effectiveness, Factor Analysis, Rehabilitation Counseling
Peer reviewedSpence, Ian; Young, Forrest W. – Psychometrika, 1978
Several nonmetric multidimensional scaling random ranking studies are discussed in response to the preceding article (TM 503 490). The choice of a starting configuration is discussed and the use of principal component analysis in obtaining such a configuration is recommended over a randomly chosen one. (JKS)
Descriptors: Correlation, Factor Analysis, Goodness of Fit, 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 reviewedAllen, Mary J. – Multivariate Behavioral Research, 1978
The factor differentiation hypothesis suggests that the factor structure of a set of tests tends to differentiate over time, becoming more complex and articulated. This experimental study provides evidence confirming that hypothesis. (Author/JKS)
Descriptors: Difficulty Level, Enlisted Personnel, Factor Analysis, Factor Structure
Peer reviewedChristoffersson, Anders – Psychometrika, 1977
A two-step weighted least squares estimator for multiple factor analysis of dichotomized variables is discussed. The estimator is based on the first and second order joint probabilities. Asymptotic standard errors and a model test are obtained by applying the Jackknife procedure. (Author)
Descriptors: Factor Analysis, Goodness of Fit, Item Analysis, Least Squares Statistics
Peer reviewedSkinner, Harvey A. – Educational and Psychological Measurement, 1977
EXPLORE is a flexible computer program for analyzing multiple data sets. The investigator has the option of focusing on the original variables, or of selecting a reduced rank solution where original variables are summarized by a principal components analysis. (Author/JKS)
Descriptors: Computer Programs, Correlation, Data Analysis, Factor Analysis
Peer reviewedDavison, Mark L. – Psychometrika, 1977
A model is presented which allows for the prediction of relationships among stimuli when stimulus responses are linearly related to squared distances between stimulus scale values and person scores along a latent continuum. Applications to developmental and attitudinal data are discussed. (Author/JKS)
Descriptors: Attitudes, Factor Analysis, Mathematical Models, Measurement
Peer reviewedOtteson, James P.; Holzman, Philip S. – Journal of Abnormal Psychology, 1976
Explores whether it is possible to isolate some of the traditional cognitive controls in a group of seriously disturbed psychiatric patients then evaluates whether various diagnostic groups differ from each other and from normals with respect to these cognitive controls. (Author/RK)
Descriptors: Cognitive Processes, Evaluative Thinking, Factor Analysis, Psychopathology
Peer reviewedCronkhite, Gary; Liska, Jo – Communication Monographs, 1976
Descriptors: Communication (Thought Transfer), Credibility, Factor Analysis, Research Criteria
Peer reviewedKaufman, Alan S.; McLean, James E. – Journal of School Psychology, 1987
Investigated factor structures of Wechsler Intelligence Scale for Children-Revised (WISC-R) and Kaufman Assessment Battery for Children (K-ABC) for 212 normal children. Findings suggest correspondence between: (1) WISC-R Verbal Comprehension and K-ABC Achievement; (2) WISC-R Perceptual Organization and K-ABC Simultaneous Processing; and (3) WISC-R…
Descriptors: Children, Comparative Testing, Factor Analysis, Factor Structure
Peer reviewedSkinner, C. J. – Psychometrika, 1984
Multivariate selection can be represented as a linear transformation in a geometric framework. In this note this approach is extended to describe the effects of selection on regression analysis and to adjust for the effects of selection using the inverse of the linear transformation. (Author/BW)
Descriptors: Factor Analysis, Geometric Concepts, Mathematical Formulas, Multiple Regression Analysis
Peer reviewedHill, Malcolm – Educational Research Quarterly, 1987
This study examines the issue of job satisfaction of college faculty from the perspective of Herzberg's "two-factor" theory and assesses the utility of the theory. Data from 1,089 full-time faculty in 20 college and university campuses supports that "intrinsic" factors contribute primarily to job satisfaction. (Author/LMO)
Descriptors: College Faculty, Correlation, Factor Analysis, Higher Education
Peer reviewedJensen, Arthur R. – Journal of Vocational Behavior, 1986
Addresses the theoretically important question of whether g is merely an artifact of the method of constructing psychometric tests and the mathematical operations of factor analysis or whether it has an authentic claim to represent some natural phenomenon that exists independently of psychometrics and factor analysis. (Author/ABB)
Descriptors: Cognitive Measurement, Construct Validity, Factor Analysis, Individual Differences
Peer reviewedBorgen, Fred H.; Barnett, David C. – Journal of Counseling Psychology, 1987
Provides an example to illustrate the clustering approach. Discusses the variety of approaches in clustering; choice of cluster analytic techniques; the steps in cluster analysis; the data features such as level, shape, and scatter, that affect cluster results; alternate clustering methods and their relative effectiveness; and applications of…
Descriptors: Behavioral Science Research, Cluster Analysis, Counseling, Factor Analysis


