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Peer reviewedNewton, Rae R.; Connelly, Cynthia Donaldson; Landsverk, John A. – Educational and Psychological Measurement, 2001
Investigated descriptive statistics for and factor validity of scores on the Revised Conflict Tactics Scale (CTS2) (M. Straus, 1979) based on the responses of 295 high-risk postpartum women. Results are similar to those obtained from a sample of college students in a previous study and support a five-factor model. (SLD)
Descriptors: Conflict, Factor Analysis, Factor Structure, Females
Peer reviewedHarshman, Richard A.; Lundy, Margaret E. – Psychometrika, 1996
Some three-way factor analysis and multidimensional scaling models incorporate the principle of parallel proportional profiles of R. B. Cattell. Proof is presented for a unique axis orientation for a more general parallel profiles model that incorporates interacting dimensions. Special cases of PARAFAC2 and CANDECOMP models are discussed. (SLD)
Descriptors: Factor Analysis, Interaction, Models, Multidimensional Scaling
Peer reviewedBernaards, Coen A.; Sijtsma, Klaas – Multivariate Behavioral Research, 2000
Using simulation, studied the influence of each of 12 imputation methods and 2 methods using the EM algorithm on the results of maximum likelihood factor analysis as compared with results from the complete data factor analysis (no missing scores). Discusses why EM methods recovered complete data factor loadings better than imputation methods. (SLD)
Descriptors: Factor Analysis, Maximum Likelihood Statistics, Questionnaires, Simulation
Peer reviewedUtsey, Shawn O. – Measurement and Evaluation in Counseling and Development, 1999
This article describes the development and validation of a short version of the Index of Race-Related Stress - Brief Version (IRSS-B). The IRRS-B is a 22-item, multidimensional measure of the race-related stress experienced by African Americans as a result of their encounters with racism. (Author/MKA)
Descriptors: Blacks, Factor Analysis, Racial Bias, Readability
Peer reviewedHancock, Gregory R.; Kuo, Wen-Ling; Lawrence, Frank R. – Structural Equation Modeling, 2001
Using higher order factor models, this article illustrates latent curve analysis for the purpose of modeling longitudinal change directly in a latent construct. Provides examples with simultaneous estimation of covariance and mean structures for a single-group and two-group structure. (SLD)
Descriptors: Analysis of Covariance, Factor Analysis, Mathematical Models
Millsap, Roger E.; Kwok, Oi-Man – Psychological Methods, 2004
Studies of factorial invariance examine whether a common factor model holds across multiple populations with identical parameter values. Partial factorial invariance exists when some, but not all, parameters are invariant. The literature on factorial invariance is unclear about what should be done if partial invariance is found. One approach to…
Descriptors: Factor Structure, Factor Analysis, Measures (Individuals), Models
Christie, Bruce; Collyer, Jenny – British Journal of Educational Technology, 2005
Multimedia technology in principle may help speakers to deliver more effective presentations. The present study examined what effectiveness might mean in terms of audience reaction. Understanding that may help educators to use multimedia more effectively themselves and to help their students to do so. Descriptors were elicited from audiences in…
Descriptors: Audience Response, Rating Scales, Factor Analysis, Audiences
Gagne, Phill; Hancock, Gregory R. – Multivariate Behavioral Research, 2006
Sample size recommendations in confirmatory factor analysis (CFA) have recently shifted away from observations per variable or per parameter toward consideration of model quality. Extending research by Marsh, Hau, Balla, and Grayson (1998), simulations were conducted to determine the extent to which CFA model convergence and parameter estimation…
Descriptors: Sample Size, Factor Analysis, Computation, Models
Warburton, Jeni; Dyer, Matthew – Educational Gerontology, 2004
This paper discusses a study that examined why older people volunteer for a research registry based at the University of Queensland, Australia. A mailed questionnaire was utilized to explore a list of reported motives developed from an in-depth qualitative phase. An exploratory factor analysis of the findings was conducted, which showed that there…
Descriptors: Foreign Countries, Volunteers, Factor Analysis, Factor Structure
Kenny, M.C. – Child Abuse and Neglect: The International Journal, 2004
Objective:: The purpose of this study was to determine teachers' self-reported knowledge of the signs and symptoms of child maltreatment, reporting procedures, legal issues surrounding child abuse and their attitudes toward corporal punishment. In addition, a factor analysis was performed on the Educators and Child Abuse Questionnaire (ECAQ)…
Descriptors: Punishment, Legal Problems, Factor Analysis, Child Abuse
Haig, Brian D. – Multivariate Behavioral Research, 2005
This article examines the methodological foundations of exploratory factor analysis (EFA) and suggests that it is properly construed as a method for generating explanatory theories. In the first half of the article it is argued that EFA should be understood as an abductive method of theory generation that exploits an important precept of…
Descriptors: Scientific Methodology, Factor Analysis, Factor Structure, Theories
Bauer, Daniel J. – Psychological Methods, 2005
Measurement invariance is a necessary condition for the evaluation of factor mean differences over groups or time. This article considers the potential problems that can arise for tests of measurement invariance when the true factor-to-indicator relationship is nonlinear (quadratic) and invariant but the linear factor model is nevertheless…
Descriptors: Statistical Analysis, Sample Size, Factor Analysis, Measurement
Krijnen, Wim P. – Psychometrika, 2006
For the confirmatory factor model a series of inequalities is given with respect to the mean square error (MSE) of three main factor score predictors. The eigenvalues of these MSE matrices are a monotonic function of the eigenvalues of the matrix gamma[subscript rho] = theta[superscript 1/2] lambda[subscript rho] 'psi[subscript rho] [superscript…
Descriptors: Factor Analysis, Scores, Matrices, Error Patterns
Maydeu-Olivares, Albert; Coffman, Donna L. – Psychological Methods, 2006
The common factor model assumes that the linear coefficients (intercepts and factor loadings) linking the observed variables to the latent factors are fixed coefficients (i.e., common for all participants). When the observed variables are participants' observed responses to stimuli, such as their responses to the items of a questionnaire, the …
Descriptors: Factor Analysis, Structural Equation Models, Item Analysis
Williams, Ben; Myerson, Joel; Hale, Sandra – Journal of the Experimental Analysis of Behavior, 2008
Despite its avowed goal of understanding individual behavior, the field of behavior analysis has largely ignored the determinants of consistent differences in level of performance among individuals. The present article discusses major findings in the study of individual differences in intelligence from the conceptual framework of a functional…
Descriptors: Intelligence, Individual Differences, Short Term Memory, Behavioral Science Research

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