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Edgar C. Merkle; Oludare Ariyo; Sonja D. Winter; Mauricio Garnier-Villarreal – Grantee Submission, 2023
We review common situations in Bayesian latent variable models where the prior distribution that a researcher specifies differs from the prior distribution used during estimation. These situations can arise from the positive definite requirement on correlation matrices, from sign indeterminacy of factor loadings, and from order constraints on…
Descriptors: Models, Bayesian Statistics, Correlation, Evaluation Methods
Merkle, Edgar C.; Fitzsimmons, Ellen; Uanhoro, James; Goodrich, Ben – Grantee Submission, 2021
Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…
Descriptors: Bayesian Statistics, Structural Equation Models, Psychometrics, Factor Analysis
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Westfall, Peter H.; Henning, Kevin S. S.; Howell, Roy D. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
This article shows how interfactor correlation is affected by error correlations. Theoretical and practical justifications for error correlations are given, and a new equivalence class of models is presented to explain the relationship between interfactor correlation and error correlations. The class allows simple, parsimonious modeling of error…
Descriptors: Psychometrics, Correlation, Error of Measurement, Structural Equation Models
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Reise, Steven P. – Multivariate Behavioral Research, 2012
Bifactor latent structures were introduced over 70 years ago, but only recently has bifactor modeling been rediscovered as an effective approach to modeling "construct-relevant" multidimensionality in a set of ordered categorical item responses. I begin by describing the Schmid-Leiman bifactor procedure (Schmid & Leiman, 1957) and highlight its…
Descriptors: Models, Factor Structure, Factor Analysis, Correlation
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Bentler, Peter M. – Psychometrika, 2009
As pointed out by Sijtsma ("in press"), coefficient alpha is inappropriate as a single summary of the internal consistency of a composite score. Better estimators of internal consistency are available. In addition to those mentioned by Sijtsma, an old dimension-free coefficient and structural equation model based coefficients are…
Descriptors: Structural Equation Models, Reliability, Psychometrics
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van Schaik, P.; Martin, S.; Vallance, M. – Journal of Computer Assisted Learning, 2012
In contexts other than immersive virtual environments, theoretical and empirical work has identified flow experience as a major factor in learning and human-computer interaction. Flow is defined as a "holistic sensation that people feel when they act with total involvement". We applied the concept of flow to modeling the experience of…
Descriptors: Structural Equation Models, Interaction, Problem Solving, Psychometrics
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Sijtsma, Klaas – Psychometrika, 2009
The critical reactions of Bentler (2009, doi: 10.1007/s11336-008-9100-1), Green and Yang (2009a, doi: 10.1007/s11336-008-9098-4 ; 2009b, doi: 10.1007/s11336-008-9099-3), and Revelle and Zinbarg (2009, doi: 10.1007/s11336-008-9102-z) to Sijtsma's (2009, doi: 10.1007/s11336-008-9101-0) paper on Cronbach's alpha are addressed. The dissemination of…
Descriptors: Psychometrics, Reliability, Theory Practice Relationship, Structural Equation Models
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Cheung, Mike W. -L. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Confidence intervals (CIs) for parameters are usually constructed based on the estimated standard errors. These are known as Wald CIs. This article argues that likelihood-based CIs (CIs based on likelihood ratio statistics) are often preferred to Wald CIs. It shows how the likelihood-based CIs and the Wald CIs for many statistics and psychometric…
Descriptors: Intervals, Structural Equation Models, Simulation, Correlation
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Ogasawara, Haruhiko – Psychometrika, 2007
Higher-order approximations to the distributions of fit indexes for structural equation models under fixed alternative hypotheses are obtained in nonnormal samples as well as normal ones. The fit indexes include the normal-theory likelihood ratio chi-square statistic for a posited model, the corresponding statistic for the baseline model of…
Descriptors: Intervals, Structural Equation Models, Goodness of Fit, Simulation
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Lee, Sik-Yum; Tang, Nian-Sheng – Psychometrika, 2004
By regarding the latent random vectors as hypothetical missing data and based on the conditional expectation of the complete-data log-likelihood function in the EM algorithm, we investigate assessment of local influence of various perturbation schemes in a nonlinear structural equation model. The basic building blocks of local influence analysis…
Descriptors: Structural Equation Models, Influences, Simulation, Psychometrics
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Li, Heng – Psychometrika, 2004
A type of data layout that may be considered as an extension of the two-way random effects analysis of variance is characterized and modeled based on group invariance. The data layout seems to be suitable for several scenarios in psychometrics, including the one in which multiple measurements are taken on each of a set of variables, and the…
Descriptors: Statistical Analysis, Psychometrics, Hypothesis Testing, Algebra
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Hazlett-Stevens, Holly; Ullman, Jodie B.; Craske, Michelle G. – Assessment, 2004
The Penn State Worry Questionnaire (PSWQ) was originally designed as a unifactorial measure of pathological trait worry. However, recent studies supported a two-factor solution with positively worded items loading on the first factor and reverse-scored items loading on a second factor. The current study compared this two-factor model to a negative…
Descriptors: Measures (Individuals), Psychometrics, Factor Structure, Questionnaires
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Jones, Susanne M.; Wirtz, John G. – Human Communication Research, 2006
Burleson and Goldsmith's (1998) comforting model suggests an appraisal-based mechanism through which comforting messages can bring about a positive change in emotional states. This study is a first empirical test of three causal linkages implied by the appraisal-based comforting model. Participants (N=258) talked about an upsetting event with a…
Descriptors: Emotional Response, Affective Behavior, Interpersonal Communication, Affective Measures
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Mehta, Paras D.; Neale, Michael C. – Psychological Methods, 2005
The article uses confirmatory factor analysis (CFA) as a template to explain didactically multilevel structural equation models (ML-SEM) and to demonstrate the equivalence of general mixed-effects models and ML-SEM. An intuitively appealing graphical representation of complex ML-SEMs is introduced that succinctly describes the underlying model and…
Descriptors: Scripts, Factor Analysis, Structural Equation Models, Modeling (Psychology)
Shin, Jongho; Espin, Christine A.; Deno, Stanley L.; McConnell, Scott – Asia Pacific Education Review, 2004
The main purpose of this paper is to demonstrate how to apply the Hierarchical Linear Modeling (HLM) technique to multi-wave Curriculum-Based Measurement (CBM) measures in modeling academic growth and assessing its relations to student-and instruction-related variables. HLM has advantages over other statistical methods (e.g., repeated measures…
Descriptors: Skill Development, Psychometrics, Learning Problems, Educational Practices