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Adrian Quintero; Emmanuel Lesaffre; Geert Verbeke – Journal of Educational and Behavioral Statistics, 2024
Bayesian methods to infer model dimensionality in factor analysis generally assume a lower triangular structure for the factor loadings matrix. Consequently, the ordering of the outcomes influences the results. Therefore, we propose a method to infer model dimensionality without imposing any prior restriction on the loadings matrix. Our approach…
Descriptors: Bayesian Statistics, Factor Analysis, Factor Structure, Sampling
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Ruscio, John; Roche, Brendan – Psychological Assessment, 2012
Exploratory factor analysis (EFA) is used routinely in the development and validation of assessment instruments. One of the most significant challenges when one is performing EFA is determining how many factors to retain. Parallel analysis (PA) is an effective stopping rule that compares the eigenvalues of randomly generated data with those for…
Descriptors: Factor Analysis, Simulation, Sampling, Correlation
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Marsh, Herbert W.; Ludtke, Oliver; Nagengast, Benjamin; Trautwein, Ulrich; Morin, Alexandre J. S.; Abduljabbar, Adel S.; Koller, Olaf – Educational Psychologist, 2012
Classroom context and climate are inherently classroom-level (L2) constructs, but applied researchers sometimes--inappropriately--represent them by student-level (L1) responses in single-level models rather than more appropriate multilevel models. Here we focus on important conceptual issues (distinctions between climate and contextual variables;…
Descriptors: Foreign Countries, Classroom Environment, Educational Research, Research Design
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Flessner, Christopher A.; Woods, Douglas W.; Franklin, Martin E.; Keuthen, Nancy J.; Piacentini, John; Cashin, Susan E.; Moore, Phoebe S. – Behavior Modification, 2007
This article describes the development and initial psychometric properties of the Milwaukee Inventory for Styles of Trichotillomania-Child Version (MIST-C), a self-report scale designed to assess styles of hair pulling in children and adolescents diagnosed with trichotillomania (TTM). Using Internet sampling procedures, the authors recruited 164…
Descriptors: Measures (Individuals), Psychometrics, Sampling, Factor Analysis
Daniel, Larry G. – 1992
Some years ago, B. Efron and his colleagues developed bootstrap resampling methods as a way of estimating the degree to which statistical results will replicate across variations in sample. A basic problem in the multivariate use of bootstrap procedures involves the requirement that the results across resamplings must be rotated to best fit in a…
Descriptors: Adults, Estimation (Mathematics), Factor Analysis, Factor Structure
Harmon, Michelle G.; And Others – 1994
The stability of a two-factor model recently proposed for the Gibb Experimental Test of Testwiseness was assessed, using confirmatory factor analysis. Designed to measure seven specific testwiseness skills with 10 items per skill, Gibb's test has been shown to discriminate between persons trained and untrained in selected testwiseness skills. Such…
Descriptors: Factor Structure, Higher Education, Models, Sampling
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Patton, Wendy; Creed, Peter; Spooner-Lane, Rebecca – Australian Journal of Career Development, 2005
This article reports on a further exploration into the reliability and validity of the shortened form of the Career Development Inventory-Australia (Creed & Patton, 2004), a career maturity measure being developed to meet the need for a shorter and more up-to-date measure to provide data on this career development construct. Data gathered from…
Descriptors: Vocational Maturity, Construct Validity, Validity, Factor Structure
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Lambert, Zarrel V.; And Others – Multivariate Behavioral Research, 1991
A method is presented that eliminates some interpretational limitations arising from assumptions implicit in the use of arbitrary rules of thumb to interpret exploratory factor analytic results. The bootstrap method is presented as a way of approximating sampling distributions of estimated factor loadings. Simulated datasets illustrate the…
Descriptors: Behavioral Science Research, Computer Simulation, Estimation (Mathematics), Factor Structure
Witta, E. Lea; Keith, Timothy Z. – 1994
Although the Wechsler Intelligence Scale for Children-Revised (WISC-R) is being rapidly replaced by the third edition of the WISC, questions concerning the construct validity of the WISC-R have not yet been resolved, including the number of factors it measures and whether the same constructs fit across all age levels. This study sought to…
Descriptors: Age Differences, Analysis of Covariance, Chi Square, Construct Validity
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Buja, Andreas; Eyuboglu, Nermin – Multivariate Behavioral Research, 1992
Use of parallel analysis (PA), a selection rule for the number-of-factors problem, is investigated from the viewpoint of permutation assessment through a Monte Carlo simulation. Results reveal advantages and limitations of PA. Tables of sample eigenvalues are included. (SLD)
Descriptors: Computer Simulation, Correlation, Factor Structure, Mathematical Models
Cole, Cornette; Schwanz, Dennis J. – 1998
This document contains two papers related to the 1993-94 Schools and Staffing Survey (SASS). The first paper documents some of the problems that were encountered during student sample selection and the methods used to resolve those problems. It also provides some suggestions to alleviate some of the problems in future SASS studies. Significant…
Descriptors: Data Collection, Elementary Secondary Education, Factor Structure, National Surveys
Shively, Joe E.; Holcomb, Zelda J. – 1981
Data collected by the Appalachia Educational Laboratory (AEL) in its 1980 Needs Assessment Project was reduced to eight marker variables for use in subsequent individual state factor analyses. These variables concern (1) high need family situations; (2) effective career education/guidance; (3) increased school capacity for working with families;…
Descriptors: Career Awareness, Career Counseling, Career Guidance, Comparative Analysis
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Smith, Glenn E.; And Others – Psychological Assessment, 1992
Using the Mayo Older Americans Normative Studies (MOANS) group (526 55-to 97-year-old adults), factor models were examined for the Wechsler Adult Intelligence Scale-Revised (WAIS-R); the Wechsler Memory Scale (WMS); and a core battery of the WAIS-R, the WMS, and the Rey Auditory-Verbal Learning Test. (SLD)
Descriptors: Construct Validity, Diagnostic Tests, Factor Structure, Intelligence