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Lawrence, Frank R.; Hancock, Gregory R. – Measurement and Evaluation in Counseling and Development, 1998
Provides an introduction to latent growth modeling (LGM), a branch of structural equation modeling that facilitates the evaluation of longitudinal change. Fundamental concepts related to growth modeling and notation are introduced; and variations, extensions, and applications of the technique are discussed. Touts LGM's versatility when considering…
Descriptors: Change, Counseling, Longitudinal Studies, Measurement Techniques
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Song, Xin-Yuan; Lee, Sik-Yum; Zhu, Hong-Tu – Structural Equation Modeling, 2001
Studied the maximum likelihood estimation of unknown parameters in a general LISREL-type model with mixed polytomous and continuous data through Monte Carlo simulation. Proposes a model selection procedure for obtaining good models for the underlying substantive theory and discusses the effectiveness of the proposed model. (SLD)
Descriptors: Maximum Likelihood Statistics, Monte Carlo Methods, Selection, Simulation
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Dolan, Conor; van der Sluis, Sophie; Grasman, Raoul – Structural Equation Modeling: A Multidisciplinary Journal, 2005
We consider power calculation in structural equation modeling with data missing completely at random (MCAR). Muth?n and Muth?n (2002) recently demonstrated how power calculations with data MCAR can be carried out by means of a Monte Carlo study. Here we show that the method of Satorra and Saris (1985), which is based on the nonnull distribution of…
Descriptors: Computation, Monte Carlo Methods, Structural Equation Models, Statistical Analysis
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Wilkinson, Ross B. – Journal of Youth and Adolescence, 2004
This paper presents the results of 3 studies examining the relationships of parental attachment, peer attachment, and self-esteem to adolescent psychological health. A model is presented in which parental attachment directly influences both psychological health and self-esteem and the influence of peer attachment on psychological health is totally…
Descriptors: Older Adults, Psychology, Structural Equation Models, Depression (Psychology)
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Bauer, Daniel J.; Curran, Patrick J. – Psychological Methods, 2004
Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…
Descriptors: Structural Equation Models, Item Response Theory, Research Methodology, Computation
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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