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Fisk, Charles L.; Harring, Jeffrey R.; Shen, Zuchao; Leite, Walter; Suen, King Yiu; Marcoulides, Katerina M. – Educational and Psychological Measurement, 2023
Sensitivity analyses encompass a broad set of post-analytic techniques that are characterized as measuring the potential impact of any factor that has an effect on some output variables of a model. This research focuses on the utility of the simulated annealing algorithm to automatically identify path configurations and parameter values of omitted…
Descriptors: Structural Equation Models, Algorithms, Simulation, Evaluation Methods
Suppanut Sriutaisuk; Yu Liu; Seungwon Chung; Hanjoe Kim; Fei Gu – Educational and Psychological Measurement, 2025
The multiple imputation two-stage (MI2S) approach holds promise for evaluating the model fit of structural equation models for ordinal variables with multiply imputed data. However, previous studies only examined the performance of MI2S-based residual-based test statistics. This study extends previous research by examining the performance of two…
Descriptors: Structural Equation Models, Error of Measurement, Programming Languages, Goodness of Fit
James Ohisei Uanhoro – Educational and Psychological Measurement, 2024
Accounting for model misspecification in Bayesian structural equation models is an active area of research. We present a uniquely Bayesian approach to misspecification that models the degree of misspecification as a parameter--a parameter akin to the correlation root mean squared residual. The misspecification parameter can be interpreted on its…
Descriptors: Bayesian Statistics, Structural Equation Models, Simulation, Statistical Inference
Liang, Xinya – Educational and Psychological Measurement, 2020
Bayesian structural equation modeling (BSEM) is a flexible tool for the exploration and estimation of sparse factor loading structures; that is, most cross-loading entries are zero and only a few important cross-loadings are nonzero. The current investigation was focused on the BSEM with small-variance normal distribution priors (BSEM-N) for both…
Descriptors: Factor Structure, Bayesian Statistics, Structural Equation Models, Goodness of Fit
Jobst, Lisa J.; Auerswald, Max; Moshagen, Morten – Educational and Psychological Measurement, 2022
Prior studies investigating the effects of non-normality in structural equation modeling typically induced non-normality in the indicator variables. This procedure neglects the factor analytic structure of the data, which is defined as the sum of latent variables and errors, so it is unclear whether previous results hold if the source of…
Descriptors: Goodness of Fit, Structural Equation Models, Error of Measurement, Factor Analysis
Yang, Yanyun; Xia, Yan – Educational and Psychological Measurement, 2019
When item scores are ordered categorical, categorical omega can be computed based on the parameter estimates from a factor analysis model using frequentist estimators such as diagonally weighted least squares. When the sample size is relatively small and thresholds are different across items, using diagonally weighted least squares can yield a…
Descriptors: Scores, Sample Size, Bayesian Statistics, Item Analysis
Aytürk, Ezgi; Cham, Heining; Jennings, Patricia A.; Brown, Joshua L. – Educational and Psychological Measurement, 2020
Methods to handle ordered-categorical indicators in latent variable interactions have been developed, yet they have not been widely applied. This article compares the performance of two popular latent variable interaction modeling approaches in handling ordered-categorical indicators: unconstrained product indicator (UPI) and latent moderated…
Descriptors: Evaluation Methods, Grade 3, Grade 4, Grade 5
Marcoulides, George A.; Emrich, Christin; Marcoulides, Laura D. – Educational and Psychological Measurement, 2008
The Computer Anxiety Scale (CAS) measures the perceptions of individuals with respect to their anxiety toward computers. Although the CAS was developed a number of years ago, research has shown that its factor structure has remained stable. Recent cross-cultural studies using samples of college students from various countries have also shown that…
Descriptors: College Students, Structural Equation Models, Computer Attitudes, Factor Structure
Fan, Weihua; Hancock, Gregory R. – Educational and Psychological Measurement, 2006
In the common two-step structural equation modeling process, modifications are routinely made to the measurement portion of the model prior to assessing structural relations. The effect of such measurement model modifications on the structural parameter estimates, however, is not well known and is the subject of the current investigation. For a…
Descriptors: Error of Measurement, Evaluation Methods, Monte Carlo Methods, Sample Size