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Showing all 11 results Save | Export
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van Laar, Saskia; Braeken, Johan – Practical Assessment, Research & Evaluation, 2021
Despite the sensitivity of fit indices to various model and data characteristics in structural equation modeling, these fit indices are used in a rigid binary fashion as a mere rule of thumb threshold value in a search for model adequacy. Here, we address the behavior and interpretation of the popular Comparative Fit Index (CFI) by stressing that…
Descriptors: Goodness of Fit, Structural Equation Models, Sampling, Sample Size
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Pavlov, Goran; Maydeu-Olivares, Alberto; Shi, Dexin – Educational and Psychological Measurement, 2021
We examine the accuracy of p values obtained using the asymptotic mean and variance (MV) correction to the distribution of the sample standardized root mean squared residual (SRMR) proposed by Maydeu-Olivares to assess the exact fit of SEM models. In a simulation study, we found that under normality, the MV-corrected SRMR statistic provides…
Descriptors: Structural Equation Models, Goodness of Fit, Simulation, Error of Measurement
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Levy, Roy – AERA Online Paper Repository, 2017
A conceptual distinction is drawn between indicators, which serve to define latent variables, and outcomes, which do not. However, commonly used frequentist and Bayesian estimation procedures do not honor this distinction. They allow the outcomes to influence the latent variables and the measurement model parameters for the indicators, rendering…
Descriptors: Bayesian Statistics, Structural Equation Models, Sampling, Goodness of Fit
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Walker, David A.; Smith, Thomas J. – Measurement and Evaluation in Counseling and Development, 2017
Nonnormality of data presents unique challenges for researchers who wish to carry out structural equation modeling. The subsequent SPSS syntax program computes bootstrap-adjusted fit indices (comparative fit index, Tucker-Lewis index, incremental fit index, and root mean square error of approximation) that adjust for nonnormality, along with the…
Descriptors: Robustness (Statistics), Sampling, Statistical Inference, Goodness of Fit
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Dilmaç, Bülent – Educational Sciences: Theory and Practice, 2017
The purpose of this research is to present the relationship of teenagers' values with their levels of cyberbullying and hopelessness, as well as to test the created model in terms of these relations. This research analyzes the predictive relationships among adolescents' values, cyberbullying, and hopelessness through the program AMOS 19 in…
Descriptors: Correlation, Psychological Patterns, Bullying, Computer Mediated Communication
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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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Lombardi, Luigi; Pastore, Massimiliano – Multivariate Behavioral Research, 2012
In many psychological questionnaires the need to analyze empirical data raises the fundamental problem of possible fake or fraudulent observations in the data. This aspect is particularly relevant for researchers working on sensitive topics such as, for example, risky sexual behaviors and drug addictions. Our contribution presents a new…
Descriptors: Deception, Measures (Individuals), Sampling, Structural Equation Models
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Larwin, Karen; Harvey, Milton – Practical Assessment, Research & Evaluation, 2012
Establishing model parsimony is an important component of structural equation modeling (SEM). Unfortunately, little attention has been given to developing systematic procedures to accomplish this goal. To this end, the current study introduces an innovative application of the jackknife approach first presented in Rensvold and Cheung (1999). Unlike…
Descriptors: Structural Equation Models, Sampling, Statistical Inference, Measures (Individuals)
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Chang, I-Hua – School Leadership & Management, 2011
The purpose of this study was to explore the relationships between distributed leadership, teachers' academic optimism and student achievement in learning. The study targeted public elementary schools in Taiwan and adopted stratified random sampling to investigate 1500 teachers. Teachers' perceptions were collected by a self-report scale. In…
Descriptors: Elementary Schools, Academic Achievement, Foreign Countries, Statistical Analysis
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Jones-Farmer, L. Allison; Pitts, Jennifer P.; Rainer, R. Kelly – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Although SAS PROC CALIS is not designed to perform multigroup comparisons, it is believed that SAS can be "tricked" into doing so for groups of equal size. At present, there are no comprehensive examples of the steps involved in performing a multigroup comparison in SAS. The purpose of this article is to illustrate these steps. We demonstrate…
Descriptors: Goodness of Fit, Structural Equation Models, Measurement Techniques, Interpersonal Communication
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La Du, Terence J.; Tanaka, J. S. – Multivariate Behavioral Research, 1995
After reviewing the multiple fit indices in structural equation models, evidence on their behavior is presented through simulation studies in which sample size, estimation method, and model misspecification varied. Two sampling studies, with and without known populations, are presented, and implications for the use of fit indices are discussed.…
Descriptors: Estimation (Mathematics), Goodness of Fit, Sample Size, Sampling