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Showing 1 to 15 of 19 results Save | Export
Cain, Meghan K.; Zhang, Zhiyong – Grantee Submission, 2018
Despite its importance to structural equation modeling, model evaluation remains underdeveloped in the Bayesian SEM framework. Posterior predictive p-values (PPP) and deviance information criteria (DIC) are now available in popular software for Bayesian model evaluation, but they remain under-utilized. This is largely due to the lack of…
Descriptors: Bayesian Statistics, Structural Equation Models, Monte Carlo Methods, Sample Size
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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
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Chen, Ruey-Shin; Liu, I-Fan – Journal of Educational Computing Research, 2017
Currently, e-learning systems are being widely used in all stages of education. However, it is difficult for school administrators to accurately assess the actual usage performance of a new system, especially when an organization wishes to update the system for users from different backgrounds using new devices such as smartphones. To allow school…
Descriptors: Educational Technology, Technology Uses in Education, College Students, Student Attitudes
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Abolfazli, Elham; Saidabadi, Reza Yousefi; Fallah, Vahid – International Education Studies, 2016
The purpose of the present study is to investigate indifference management structural model in education system of Ardabil Province. The research method was integration study using Alli modeling. Statistical society of research was 420 assistant professors of educational science, managers, and deputies of Ardabil's second period of high schools…
Descriptors: Sampling, Structural Equation Models, Questionnaires, Computer Software
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Finch, W. Holmes; Bronk, Kendall Cotton – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Latent class analysis (LCA) is an increasingly popular tool that researchers can use to identify latent groups in the population underlying a sample of responses to categorical observed variables. LCA is most commonly used in an exploratory fashion whereby no parameters are specified a priori. Although this exploratory approach is reasonable when…
Descriptors: Structural Equation Models, Computer Software, Programming, Goodness of Fit
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Bryant, Fred B.; Satorra, Albert – Structural Equation Modeling: A Multidisciplinary Journal, 2012
We highlight critical conceptual and statistical issues and how to resolve them in conducting Satorra-Bentler (SB) scaled difference chi-square tests. Concerning the original (Satorra & Bentler, 2001) and new (Satorra & Bentler, 2010) scaled difference tests, a fundamental difference exists in how to compute properly a model's scaling correction…
Descriptors: Statistical Analysis, Structural Equation Models, Goodness of Fit, Least Squares Statistics
Cakar, Bekir – ProQuest LLC, 2011
The situations and problems that police officers face are more complex in today's society, due in part to the increase of technology and growing complexity of globalization. Accordingly, to solve these problems and deal with the complexities, law enforcement organizations develop and apply new techniques and methods such as geographic information…
Descriptors: Police, Geographic Information Systems, Law Enforcement, Foreign Countries
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Shittu, Ahmed Tajudeen; Basha, Kamal Madarsha; AbdulRahman, Nik Suryani Nik; Ahmad, Tunku Badariah Tunku – Multicultural Education & Technology Journal, 2011
Purpose: Social software usage is growing at an exponential rate among the present generation of students. Yet, there is paucity of empirical study to understand the determinant of its use in the present setting of this study. This study, therefore, seeks to investigate factors that predict students' attitudes and intentions to use this…
Descriptors: Student Attitudes, Prediction, Internet, Foreign Countries
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Bai, Yun; Poon, Wai-Yin – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Two-level data sets are frequently encountered in social and behavioral science research. They arise when observations are drawn from a known hierarchical structure, such as when individuals are randomly drawn from groups that are randomly drawn from a target population. Although 2-level data analysis in the context of structural equation modeling…
Descriptors: Structural Equation Models, Data Analysis, Simulation, Goodness of Fit
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Herzog, Walter; Boomsma, Anne – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Traditional estimators of fit measures based on the noncentral chi-square distribution (root mean square error of approximation [RMSEA], Steiger's [gamma], etc.) tend to overreject acceptable models when the sample size is small. To handle this problem, it is proposed to employ Bartlett's (1950), Yuan's (2005), or Swain's (1975) correction of the…
Descriptors: Intervals, Sample Size, Monte Carlo Methods, Computation
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Savalei, Victoria; Kolenikov, Stanislav – Psychological Methods, 2008
Recently, R. D. Stoel, F. G. Garre, C. Dolan, and G. van den Wittenboer (2006) reviewed approaches for obtaining reference mixture distributions for difference tests when a parameter is on the boundary. The authors of the present study argue that this methodology is incomplete without a discussion of when the mixtures are needed and show that they…
Descriptors: Structural Equation Models, Goodness of Fit, Evaluation Methods, Statistical Analysis
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Asparouhov, Tihomir; Muthen, Bengt – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Exploratory factor analysis (EFA) is a frequently used multivariate analysis technique in statistics. Jennrich and Sampson (1966) solved a significant EFA factor loading matrix rotation problem by deriving the direct Quartimin rotation. Jennrich was also the first to develop standard errors for rotated solutions, although these have still not made…
Descriptors: Structural Equation Models, Testing, Factor Analysis, Research Methodology
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Schumacker, Randall E. – Structural Equation Modeling: A Multidisciplinary Journal, 2006
Amos 5.0 (Arbuckle, 2003) permits exploratory specification searches for the best theoretical model given an initial model using the following fit function criteria: chi-square (C), chi-square--df (C--df), Akaike Information Criteria (AIC), Browne-Cudeck criterion (BCC), Bayes Information Criterion (BIC) , chi-square divided by the degrees of…
Descriptors: Computer Software, Structural Equation Models, Models, Search Strategies
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van Buuren, Stef – Psychometrika, 1997
This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)
Descriptors: Computer Software, Goodness of Fit, Maximum Likelihood Statistics, Structural Equation Models
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Dolan, Conor; Bechger, Timo; Molenaar, Peter – Structural Equation Modeling, 1999
Considers models incorporating principal components from the perspectives of structural-equation modeling. These models include the following: (1) the principal-component analysis of patterned matrices; (2) multiple analysis of variance based on principal components; and (3) multigroup principal-components analysis. Discusses fitting these models…
Descriptors: Computer Software, Factor Analysis, Goodness of Fit, Matrices
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