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Showing 16 to 30 of 258 results Save | Export
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Dombrowski, Stefan C.; McGill, Ryan J.; Canivez, Gary L. – School Psychology Quarterly, 2018
The Woodcock-Johnson (fourth edition; WJ IV; Schrank, McGrew, & Mather, 2014a) was recently redeveloped and retains its linkage to Cattell-Horn-Carroll theory (CHC). Independent reviews (e.g., Canivez, 2017) and investigations (Dombrowski, McGill, & Canivez, 2017) of the structure of the WJ IV full test battery and WJ IV Cognitive have…
Descriptors: Factor Analysis, Achievement Tests, Cognitive Tests, Cognitive Ability
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Hutton, Disraeli M. – International Journal of Leadership in Education, 2018
The study explored critical factors that explain leadership performance of high-performing principals and examined the relationship between these factors based on the ratings of school constituents in the public school system. The principal component analysis with the use of Varimax Rotation revealed that four components explain 51.1% of the…
Descriptors: Principals, Leadership Qualities, Correlation, School Effectiveness
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Dombrowski, Stefan C. – Journal of Psychoeducational Assessment, 2014
The Woodcock-Johnson-III cognitive in the adult time period (age 20 to 90 plus) was analyzed using exploratory bifactor analysis via the Schmid-Leiman orthogonalization procedure. The results of this study suggested possible overfactoring, a different factor structure from that posited in the Technical Manual and a lack of invariance across both…
Descriptors: Cognitive Tests, Adults, Factor Analysis, Factor Structure
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Adachi, Kohei – Psychometrika, 2013
Rubin and Thayer ("Psychometrika," 47:69-76, 1982) proposed the EM algorithm for exploratory and confirmatory maximum likelihood factor analysis. In this paper, we prove the following fact: the EM algorithm always gives a proper solution with positive unique variances and factor correlations with absolute values that do not exceed one,…
Descriptors: Factor Analysis, Mathematics, Correlation, Maximum Likelihood Statistics
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Myers, Nicholas D.; Ahn, Soyeon; Jin, Ying – Structural Equation Modeling: A Multidisciplinary Journal, 2013
The purpose of this study was to explore the influence of the number of targets specified on the quality of exploratory factor analysis solutions with a complex underlying structure and incomplete substantive measurement theory. Three Monte Carlo studies were performed based on the ratio of the number of observed variables to the number of…
Descriptors: Factor Analysis, Monte Carlo Methods, Sample Size, Measurement
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Beavers, Amy S.; Lounsbury, John W.; Richards, Jennifer K.; Huck, Schuyler W.; Skolits, Gary J.; Esquivel, Shelley L. – Practical Assessment, Research & Evaluation, 2013
The uses and methodology of factor analysis are widely debated and discussed, especially the issues of rotational use, methods of confirmatory factor analysis, and adequate sample size. The variety of perspectives and often conflicting opinions can lead to confusion among researchers about best practices for using factor analysis. The focus of the…
Descriptors: Factor Analysis, Educational Research, Best Practices, Sample Size
Ritter, Nicola L. – Online Submission, 2012
Many researchers recognize that factor analysis can be conducted on both correlation matrices and variance-covariance matrices. Although most researchers extract factors from non-distribution free or parametric methods, researchers can also extract factors from distribution free or non-parametric methods. The nature of the data dictates the method…
Descriptors: Factor Analysis, Comparative Analysis, Correlation, Nonparametric Statistics
Goodwyn, Fara – Online Submission, 2012
Exploratory factor analysis involves five key decisions. The second decision, how many factors to retain, is the focus of the current paper. Extracting too many or too few factors often leads to devastating effects on study results. The advantages and disadvantages of the most effective and/or most utilized strategies to determine the number of…
Descriptors: Syntax, Factor Analysis, Research Methodology, Statistical Analysis
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Wetzel, Eunike; Xu, Xueli; von Davier, Matthias – Educational and Psychological Measurement, 2015
In large-scale educational surveys, a latent regression model is used to compensate for the shortage of cognitive information. Conventionally, the covariates in the latent regression model are principal components extracted from background data. This operational method has several important disadvantages, such as the handling of missing data and…
Descriptors: Surveys, Regression (Statistics), Models, Research Methodology
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Schneider, W. Joel – Journal of Psychoeducational Assessment, 2013
Researchers often argue that the structural models of the constructs they study are relevant to clinicians. Unfortunately, few clinicians are able to translate the mathematically precise relationships between latent constructs and observed scores into information that can be usefully applied to individuals. Typically this means that when a new…
Descriptors: Factor Analysis, Psychological Studies, Cognitive Ability, Test Reliability
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Ananda B. W. Manage; Stephen M. Scariano – Journal of Statistics Education, 2013
Principal Component Analysis is widely used in applied multivariate data analysis, and this article shows how to motivate student interest in this topic using cricket sports data. Here, principal component analysis is successfully used to rank the cricket batsmen and bowlers who played in the 2012 Indian Premier League (IPL) competition. In…
Descriptors: Factor Analysis, Multivariate Analysis, Data Analysis, Student Interests
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Pronk, Jeroen; Olthof, Tjeert; Goossens, Frits A. – Journal of Early Adolescence, 2015
This study investigated personality correlates of early adolescents' tendency to either defend victims of bullying or to avoid involvement in bullying situations. Participants were 591 Dutch fifth- and sixth-grade students (X-bar[subscript age] = 11.42 years). Hierarchical regression models were run to predict these students' peer-reported…
Descriptors: Personality Traits, Correlation, Bullying, Victims
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Baksalary, Oskar Maria; Trenkler, Gotz – International Journal of Mathematical Education in Science and Technology, 2010
By considering a general representation of proper rotation matrices, the eigenvalues and eigenspaces of those matrices are identified.
Descriptors: Matrices, Algebra, Factor Analysis, Spatial Ability
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Bentler, Peter M.; Yuan, Ke-Hai – Psychometrika, 2011
Indefinite symmetric matrices that are estimates of positive-definite population matrices occur in a variety of contexts such as correlation matrices computed from pairwise present missing data and multinormal based methods for discretized variables. This note describes a methodology for scaling selected off-diagonal rows and columns of such a…
Descriptors: Scaling, Factor Analysis, Correlation, Predictor Variables
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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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