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Marsh, Herbert W.; Wen, Zhonglin; Hau, Kit-Tai – Psychological Methods, 2004
Interactions between (multiple indicator) latent variables are rarely used because of implementation complexity and competing strategies. Based on 4 simulation studies, the traditional constrained approach performed more poorly than did 3 new approaches-unconstrained, generalized appended product indicator, and quasi-maximum-likelihood (QML). The…
Descriptors: Structural Equation Models, Item Analysis, Error Patterns, Computation
Cole, David A.; Martin, Nina C.; Steiger, James H. – Psychological Methods, 2005
The latent trait-state-error model (TSE) and the latent state-trait model with autoregression (LST-AR) represent creative structural equation methods for examining the longitudinal structure of psychological constructs. Application of these models has been somewhat limited by empirical or conceptual problems. In the present study, Monte Carlo…
Descriptors: Structural Equation Models, Computation, Longitudinal Studies, Monte Carlo Methods
van der Sluis, Sophie; Dolan, Conor V.; Stoel, Reinoud D. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
This article is concerned with the seemingly simple problem of testing whether latent factors are perfectly correlated (i.e., statistically indistinct). In recent literature, researchers have used different approaches, which are not always correct or complete. We discuss the parameter constraints required to obtain such perfectly correlated latent…
Descriptors: Testing, Factor Structure, Structural Equation Models, Correlation
Lee, Sik-Yum; Lu, Bin – Multivariate Behavioral Research, 2003
In this article, a case-deletion procedure is proposed to detect influential observations in a nonlinear structural equation model. The key idea is to develop the diagnostic measures based on the conditional expectation of the complete-data log-likelihood function in the EM algorithm. An one-step pseudo approximation is proposed to reduce the…
Descriptors: Structural Equation Models, Computation, Mathematics, Simulation
Ferrer, Emilio; McArdle, John – Structural Equation Modeling: A Multidisciplinary Journal, 2003
Structural equation models are presented as alternative models for examining longitudinal data. The models include (a) a cross-lagged regression model, (b) a factor model based on latent growth curves, and (c) a dynamic model based on latent difference scores. The illustrative data are on motivation and perceived competence of students during…
Descriptors: Models, Data Analysis, Structural Equation Models, Longitudinal Studies
Peugh, James L.; Enders, Craig K. – Educational and Psychological Measurement, 2005
Beginning with Version 11, SPSS implemented the MIXED procedure, which is capable of performing many common hierarchical linear model analyses. The purpose of this article was to provide a tutorial for performing cross-sectional and longitudinal analyses using this popular software platform. In doing so, the authors borrowed heavily from Singer's…
Descriptors: Computer Software, Statistical Analysis, Causal Models, Structural Equation Models
Kember, David; Leung, Doris Y. P. – Studies in Higher Education, 2005
Surveys at a university in Hong Kong indicated that graduates of discrete part-time programmes perceived significantly higher development in eight out of nine graduate capabilities than their counterparts in full-time programmes. Several possible explanations are considered and rejected. The conventional view that capabilities are nurtured through…
Descriptors: Foreign Countries, Teaching Methods, Active Learning, Structural Equation Models
Asparouhov, Tihomir – Structural Equation Modeling, 2005
This article reviews several basic statistical tools needed for modeling data with sampling weights that are implemented in Mplus Version 3. These tools are illustrated in simulation studies for several latent variable models including factor analysis with continuous and categorical indicators, latent class analysis, and growth models. The…
Descriptors: Probability, Structural Equation Models, Sampling, Least Squares Statistics
Schoonen, Rob – Language Testing, 2005
The assessment of writing ability is notoriously difficult. Different facets of the assessment seem to influence its outcome. Besides the writer's writing proficiency, the topic of the assignment, the features or traits scored (e.g., content or language use) and even the way in which these traits are scored (e.g., holistically or analytically)…
Descriptors: Grade 6, Scoring, Essays, Writing Ability
Derryberry, W. Pitt; Thoma, Stephen J. – Merrill-Palmer Quarterly: Journal of Developmental Psychology, 2005
Current models of moral functioning such as those of Rest (1983) and Damon and Hart (1988) have maintained that optimal moral development and consistent moral action require the presence of multiple constructs. In order to examine the importance of the presence of multiple variables relevant to moral functioning, structural equation modeling was…
Descriptors: Value Judgment, Structural Equation Models, Moral Development, College Students
Raykov, Tenko – Structural Equation Modeling, 2004
A widely and readily applicable covariance structure modeling approach is outlined that allows point and interval estimation of scale reliability with fixed components. The procedure employs only linear constraints introduced in a congeneric model, which after reparameterization permit expression of composite reliability as a function of…
Descriptors: Measures (Individuals), Intervals, Error of Measurement, Structural Equation Models
Raykov, Tenko; Marcoulides, George A. – Structural Equation Modeling, 2004
In applications of structural equation modeling, it is often desirable to obtain measures of uncertainty for special functions of model parameters. This article provides a didactic discussion of how a method widely used in applied statistics can be employed for approximate standard error and confidence interval evaluation of such functions. The…
Descriptors: Intervals, Structural Equation Models, Evaluation Methods, Statistical Analysis
Oh, Hyeon-Joo; Glutting, Joseph J.; Watkins, Marley W.; Youngstrom, Eric A.; McDermott, Paul A. – Journal of Special Education, 2004
In this study, the authors used structural equation modeling to investigate relationships between ability constructs from the "Wechsler Intelligence Scale for Children-Third Edition" (WISC-III; Wechsler, 1991) in explaining reading and mathematics achievement constructs on the "Wechsler Individual Achievement Test" (WIAT;…
Descriptors: Psychologists, Structural Equation Models, Mathematics Achievement, Intelligence
Betz, Nancy E. – Counseling Psychologist, 2005
The present reaction responds to the three research-related core articles in the Scientific Forum of the May 2005 issue of "The Counseling Psychologist." I agree that too few of our studies are based on theories or models. Using the nomological network, I suggest how research ideas can more readily be depicted to allow model and theory testing. I…
Descriptors: Structural Equation Models, Productivity, Counseling Psychology, Periodicals
Park, Ilhyeok; Schutz, Robert W. – Research Quarterly for Exercise and Sport, 2005
The purpose of this paper is to introduce the Latent Growth Model (LGM) to researchers in exercise and sport science. Although the LGM has several merits over traditional analysis techniques in analyzing change and was first introduced almost 20 years ago, it is still underused in exercise and sport science research. This statistical model can be…
Descriptors: Physical Fitness, Structural Equation Models, Exercise Physiology, Measurement Techniques