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Liu, Yan; Zumbo, Bruno D. – Educational and Psychological Measurement, 2012
There is a lack of research on the effects of outliers on the decisions about the number of factors to retain in an exploratory factor analysis, especially for outliers arising from unintended and unknowingly included subpopulations. The purpose of the present research was to investigate how outliers from an unintended and unknowingly included…
Descriptors: Factor Analysis, Factor Structure, Evaluation Research, Evaluation Methods
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Henson, Robin K.; Roberts, J. Kyle – Educational and Psychological Measurement, 2006
Given the proliferation of factor analysis applications in the literature, the present article examines the use of factor analysis in current published research across four psychological journals. Notwithstanding ease of analysis due to computers, the appropriate use of factor analysis requires a series of thoughtful researcher judgments. These…
Descriptors: Factor Analysis, Psychological Studies, Literature Reviews, Research Methodology
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Budescu, David V. – Educational and Psychological Measurement, 1983
The degree of indeterminacy of the factor score estimates is biased and can lead to erroneous conclusion regarding the nature of the results. The magnitude of this bias is illustrated and guidelines for describing factor analytic studies using factor scores are offered. (Author/PN)
Descriptors: Correlation, Estimation (Mathematics), Factor Analysis, Factor Structure
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Hollenbeck, George P. – Educational and Psychological Measurement, 1972
The Little Jiffy" consists of principal components analysis and varimax rotation of all components with eigenvalues greater than one. (DG)
Descriptors: Cognitive Development, Comparative Analysis, Factor Analysis, Factor Structure
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Terranova, Carmelo – Educational and Psychological Measurement, 1971
A computer program designed to compare factors from similar concept matrices (person by scale) obtained at different times is presented. (PR)
Descriptors: Attitude Change, Comparative Analysis, Computer Programs, Factor Structure
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Glorfeld, Louis W. – Educational and Psychological Measurement, 1995
A modification of Horn's parallel analysis is introduced that is based on the Monte Carlo simulation of the null distributions of the eigenvalues generated from a population correlation identity matrix. This modification reduces the tendency of the parallel analysis procedure to overextract or to extract poorly defined factors. (SLD)
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices
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Hogarty, Kristine Y.; Hines, Constance V.; Kromrey, Jeffrey D.; Ferron, John M.; Mumford, Karen R. – Educational and Psychological Measurement, 2005
The purpose of this study was to investigate the relationship between sample size and the quality of factor solutions obtained from exploratory factor analysis. This research expanded upon the range of conditions previously examined, employing a broad selection of criteria for the evaluation of the quality of sample factor solutions. Results…
Descriptors: Sample Size, Factor Analysis, Factor Structure, Evaluation Methods
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Mace, David E.; And Others – Educational and Psychological Measurement, 1985
Through use of confirmatory maximum likelihood factor analysis in conjunction with the LISREL V computer program, an evaluation was made of the validity of higher-order ability constructs in structure-of-intellect tests all containing semantic content and operations of cognition or evaluation. (Author/DWH)
Descriptors: Academic Aptitude, Aptitude Tests, Factor Analysis, Factor Structure
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Kerlinger, Fred N. – Educational and Psychological Measurement, 1972
The theoretical expectations of duality of attitude structure and comparative lack of bipolarity have now been found using both R and Q methodologies. (Author)
Descriptors: Attitude Measures, Data Analysis, Factor Analysis, Factor Structure
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Piotrowski, Chris – Educational and Psychological Measurement, 1983
The present study compared the factor structures obtained when the same data were factor analyzed: (1) for the total sample (463 fifth grade students) and by sex for collapsed concepts, and (2) by individual concept for the total sample by sex, and for internal and external locus of control groups. (Author/PN)
Descriptors: Factor Analysis, Factor Structure, Individual Differences, Intermediate Grades