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Zwick, William R. – Multivariate Behavioral Research, 1982
The performance of four rules for determining the number of components (factors) to retain (Kaiser's eigenvalue greater than one, Cattell's scree, Bartlett's test, and Velicer's Map) was investigated across four systematically varied factors (sample size, number of variables, number of components, and component saturation). (Author/JKS)
Descriptors: Algorithms, Data Analysis, Factor Analysis, Factor Structure
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Badian, Nathlie A. – Journal of Special Education, 1982
All preschool children (N=180) of the same age group in a small town were tested six months before kindergarten entry with the Holbrook Screening Battery which correctly identified 92 percent of Ss scoring as both good and poor readers four years later on the Stanford Achievement Test. (Author/CL)
Descriptors: Age Differences, Factor Analysis, Language Acquisition, Prediction
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Thompson, Bruce; Pitts, Murray C. – Journal of Experimental Education, 1981
Adequacy coefficients can be derived by calculating the cosines of the angles between factors' actual and theoretically expected locations within factor space. The use of adequacy coefficients during instrument development is discussed. The development of an instrument to measure thinking interests provides a heuristic framework for the…
Descriptors: Cognitive Style, Factor Analysis, Mathematical Models, Test Construction
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McDonald, Roderick P. – Psychometrika, 1981
An expression is given for weighted least squares estimators of oblique common factors of factor analyses, constrained to have the same covariance matrix as the factors they estimate. A proof of the uniqueness of the solution is given. (Author/JKS)
Descriptors: Analysis of Covariance, Factor Analysis, Least Squares Statistics, Mathematical Models
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Revelle, William; Rocklin, Thomas – Multivariate Behavioral Research, 1979
A new procedure for determining the optimal number of interpretable factors to extract from a correlation matrix is introduced and compared to more conventional procedures. The new method evaluates the magnitude of the very simple structure index of goodness of fit for factor solutions of increasing rank. (Author/CTM)
Descriptors: Factor Analysis, Goodness of Fit, Hypothesis Testing, Research Design
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Muthen, Bengt – Psychometrika, 1978
A new method--similar to Christoffersson's--for the factor analysis of dichotomous variables uses information from the first and second order proportions to fit a multiple factor model. The estimation is considerably simplified. Items from Rotter's locus of control inventory are included. (Author/JKS)
Descriptors: Correlation, Factor Analysis, Item Analysis, Personality Measures
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Newman, Isadore; Fraas, John – Multiple Linear Regression Viewpoints, 1979
Issues in the application of multiple regression analysis as a data analytic tool are discussed at some length. Included are discussions on component regression, factor regression, ridge regression, and systems of equations. (JKS)
Descriptors: Correlation, Factor Analysis, Multiple Regression Analysis, Research Design
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Pierce, Robert C. – Journal of Leisure Research, 1980
Studies were conducted to determine personal satisfactions individuals obtained from leisure activities that were not obtained from work activities. Results of samples indicated that the four primary motivations were intimacy, relaxation, achievement, and power. Additional satisfactions included novelty, intellectual enjoyment, sociability, and…
Descriptors: Factor Analysis, Job Satisfaction, Leisure Time, Motivation
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Pierce, Robert C. – Journal of Leisure Research, 1980
Studies were conducted to rate the aptness of favorite leisure and work activities to the characteristics of individuals participating in these activities. Ratings were cluster analyzed and the results compared. Four dimensions which appeared in both work and leisure activities were destructiveness, cerebration, fulfillment, and flamboyance. (JN)
Descriptors: Cluster Analysis, Factor Analysis, Leisure Time, Personality Traits
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Sternberg, Robert J. – Journal of Educational Psychology, 1981
The decline of the psychometric paradigm for studying intelligence was due in part to its failure to meet four challenges. On the surface, users of the information-processing paradigms seem successfully to have met these challenges, but at a deeper level, the level of success is not so great. (Author/BW)
Descriptors: Cognitive Measurement, Cognitive Processes, Comparative Analysis, Correlation
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Watts, Fraser N.; Everitt, Brian S. – Journal of Clinical Psychology, 1980
The pattern of correlations between subtests suggests that several of the aptitudes are of doubtful validity. In no case was it possible to extract more than three adequately determined factors. (Author)
Descriptors: Aptitude Tests, Factor Analysis, Predictive Measurement, Test Construction
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DeLeeuw, Jan; Kroonenberg, Peter M. – Psychometrika, 1980
A new method to estimate the parameters of Tucker's three mode principal component model is discussed, and the convergence properties of the alternating least squares algorithm to solve the estimation problem are considered. An example is presented. (Author/JKS)
Descriptors: Algorithms, Factor Analysis, Least Squares Statistics, Measurement
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Newman, Ian M.; DiSalvo, Vincent S. – Journal of School Health, 1980
The values of computer-based content analysis techniques and the application of a variety of analytical methods in areas related to health education are discussed. (JD)
Descriptors: Behavioral Science Research, Computers, Content Analysis, Factor Analysis
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Bentler, P. M.; Woodward, Arthur J. – Psychometrika, 1980
A chain of lower bound inequalities leading to the greatest lower bound to reliability is established for the internal consistency of a composite of unit-weighted scores (such as a test). Algorithms for obtaining various reliability coefficients are presented. (Author/JKS)
Descriptors: Factor Analysis, Item Analysis, Measurement Techniques, Test Construction
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Woehlke, Paula; Ohara, Takeshi – Educational and Psychological Measurement, 1980
To assess the stability of the factor structure of the Instructional Improvement Questionnaire (IIQ), factor analyses were run for 1973, 1974, and 1975 results, partialling out three variables: expected grade, percent taking the course as an elective, and student's year. The factors were stable over the three years. (Author/BW)
Descriptors: Factor Analysis, Factor Structure, Questionnaires, Student Evaluation of Teacher Performance
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