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Kelvin T. Afolabi; Timothy R. Konold – Practical Assessment, Research & Evaluation, 2024
Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given…
Descriptors: Measurement Techniques, Factor Analysis, Structural Equation Models, Comparative Analysis
Manuel T. Rein; Jeroen K. Vermunt; Kim De Roover; Leonie V. D. E. Vogelsmeier – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Researchers often study dynamic processes of latent variables in everyday life, such as the interplay of positive and negative affect over time. An intuitive approach is to first estimate the measurement model of the latent variables, then compute factor scores, and finally use these factor scores as observed scores in vector autoregressive…
Descriptors: Measurement Techniques, Factor Analysis, Scores, Validity
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
Paek, Insu; Cui, Mengyao; Öztürk Gübes, Nese; Yang, Yanyun – Educational and Psychological Measurement, 2018
The purpose of this article is twofold. The first is to provide evaluative information on the recovery of model parameters and their standard errors for the two-parameter item response theory (IRT) model using different estimation methods by Mplus. The second is to provide easily accessible information for practitioners, instructors, and students…
Descriptors: Item Response Theory, Computation, Factor Analysis, Statistical Analysis
Hancock, Gregory R.; An, Ji – Educational Measurement: Issues and Practice, 2018
In this ITEMS module, we frame the topic of scale reliability within a "confirmatory factor analysis" and "structural equation modeling" (SEM) context and address some of the limitations of Cronbach's a. This modeling approach has two major advantages: (1) it allows researchers to make explicit the relation between their items…
Descriptors: Reliability, Structural Equation Models, Factor Analysis, Correlation
Malmberg, Lars-Erik – International Journal of Research & Method in Education, 2020
With a growing interest in research on educational processes, there is a need to overview suitable latent variable models for students' learning experiences in real-time. This tutorial provides an introduction to intraindividual (multilevel) structural equation models (ISEM) for the analysis of process data (e.g. intensive longitudinal,…
Descriptors: Structural Equation Models, Learning Experience, Educational Research, Personal Autonomy
Nik Nazli, Nik Nadian Nisa; Sheikh Khairudin, Sheikh Muhamad Hizam – Journal of Workplace Learning, 2018
Purpose: This paper aims to identify the relationship between organizational learning culture, psychological contract breach, work engagement, training simulation and transfer of training, to examine the effect of transfer of training on organizational citizenship behaviour and to determine the mediating effect of transfer of training on the…
Descriptors: Transfer of Training, Workplace Learning, Foreign Countries, Correlation
Ravand, Hamdollah; Baghaei, Purya – Practical Assessment, Research & Evaluation, 2016
Structural equation modeling (SEM) has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and…
Descriptors: Least Squares Statistics, Structural Equation Models, Nonparametric Statistics, Sample Size
Savi Çakar, Firdevs; Tagay, Özlem – Educational Sciences: Theory and Practice, 2017
This research is a descriptive study based on the testing of a structural model developed by considering the effects of perceived social support and subjective well-being on adolescents' risky behaviors, and the possible mediating role of self-esteem. Participants consisted of 676 high school students attending formal education institutions,…
Descriptors: Self Esteem, Social Support Groups, Risk, Health Behavior
Yildirim, Irfan – Education, 2015
The aim of the study was to determine the correlation between self-efficacy and job satisfaction among the physical education teachers. The study was carried out in correlational survey model and the study sample was made up by 306 physical education teachers who worked in different geographical regions of Turkey. The data were assessed using SPSS…
Descriptors: Physical Education, Physical Education Teachers, Job Satisfaction, Self Efficacy
Mittal, Sanjiv; Gera, Rajat; Batra, Dharminder Kumar – Education & Training, 2015
Purpose: There is a debate in literature about the generalizability of the structure and the validity of the measures of Student Evaluation of Teaching Effectiveness (SET). This debate spans the dimensionality and validity of the construct, and the use of the measure for summative and formative purposes of teachers valuation and feedback. The…
Descriptors: Foreign Countries, Student Evaluation of Teacher Performance, Measures (Individuals), Teacher Competencies
Wainer, Howard – Journal of Educational and Behavioral Statistics, 2011
This article presents an interview with Karl Gustav Joreskog. Karl Gustav Joreskog was born in Amal, Sweden, on April 25, 1935. He did his undergraduate studies at Uppsala University from 1955 to 1957, with a major in mathematics and physics. He received a PhD in statistics at Uppsala University in 1963, and he was a research statistician at…
Descriptors: Statistics, Structural Equation Models, Computer Software, Factor Analysis
Siren, Charlotta A. – Learning Organization, 2012
Purpose: The strategic learning perspective has attracted increased interest among strategic management scholars, yet the operationalisation of this concept is still in its infancy. The aim of this study is to develop a multidimensional understanding of the strategic learning process and to build an instrument to measure this concept.…
Descriptors: Learning, Strategic Planning, Computer Software, Corporations
A Second-Order Conditionally Linear Mixed Effects Model with Observed and Latent Variable Covariates
Harring, Jeffrey R.; Kohli, Nidhi; Silverman, Rebecca D.; Speece, Deborah L. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
A conditionally linear mixed effects model is an appropriate framework for investigating nonlinear change in a continuous latent variable that is repeatedly measured over time. The efficacy of the model is that it allows parameters that enter the specified nonlinear time-response function to be stochastic, whereas those parameters that enter in a…
Descriptors: Models, Statistical Analysis, Structural Equation Models, Factor Analysis
Boker, Steven; Neale, Michael; Maes, Hermine; Wilde, Michael; Spiegel, Michael; Brick, Timothy; Spies, Jeffrey; Estabrook, Ryne; Kenny, Sarah; Bates, Timothy; Mehta, Paras; Fox, John – Psychometrika, 2011
OpenMx is free, full-featured, open source, structural equation modeling (SEM) software. OpenMx runs within the "R" statistical programming environment on Windows, Mac OS-X, and Linux computers. The rationale for developing OpenMx is discussed along with the philosophy behind the user interface. The OpenMx data structures are…
Descriptors: Structural Equation Models, Open Source Technology, Computer Software, Models
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