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Structural Equation Modeling
Abstract
The first half of this chapter presents an overview of the type hypotheses, statistical theory, and major issues relevant to specifying, estimating, evaluating, and interpreting structural equation models. Following this brief SEM overview, a complete example of a simple SEM model of risky behavior using a large dataset of responses from preteen children is presented. This presentation includes examples of output from EQS 6.1. The second half of chapter is devoted to a detailed presentation of the current issues and important future research directions in structural equation modeling.
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“SEM was chosen as the method to examine the data above the use of multiple regression or simple correlations, as the method allowed for the latent modelling of variables with measurement error taken into account (Ullman & Bentler, 2012).”
From Sources and effects of foreign language enjoyment, anxiety, and boredom: A structural equation modeling approach (2023) · cites this paper as Ullman & Bentler, 2012
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O’Boyle, E. H., & Williams, L. J. (2011) · Journal of Applied Psychology · doi:10.1037/a0020539 · Cited by 135
Testing Model Nesting and Equivalence
Bentler, P., & Satorra, A. (2008) · Psychological methods · doi:10.1037/a0019625 · Cited by 133
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Maydeu‐Olivares, A., Coffman, D. L., & Hartmann, W. M. (2007) · Psychological Methods · doi:10.1037/1082-989x.12.2.157 · Cited by 130
The Reliability Paradox in Assessing Structural Relations Within Covariance Structure Models
Hancock, G. R., & Mueller, R. O. (2011) · Educational and Psychological Measurement · doi:10.1177/0013164410384856 · Cited by 130
Evaluation of Scale Reliability With Binary Measures Using Latent Variable Modeling
Raykov, T., Dimitrov, D. M., & Asparouhov, T. (2010) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511003659417 · Cited by 127
Robust mean and covariance structure analysis
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Self-citationMultilevel Regression Mixture Analysis
Muthén, B., & Asparouhov, T. (2009) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2009.00589.x · Cited by 125
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ML Versus MI for Missing Data With Violation of Distribution Conditions
Yuan, K., Yang‐Wallentin, F., & Bentler, P. M. (2012) · Sociological Methods & Research · doi:10.1177/0049124112460373 · Cited by 119
Self-citationAguinis, H., Pierce, C. A., & Culpepper, S. A. (2008) · Organizational Research Methods · doi:10.1177/1094428108318065 · Cited by 116
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Self-citationFormative Constructs Implemented via Common Factors
Treiblmaier, H., Bentler, P. M., & Mair, P. (2011) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2011.532693 · Cited by 107
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Ridge structural equation modelling with correlation matrices for ordinal and continuous data
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Self-citationProportional structural effects of formative indicators
Franke, G. R., Preacher, K. J., & Rigdon, E. E. (2008) · Journal of Business Research · doi:10.1016/j.jbusres.2008.01.011 · Cited by 103
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Self-citationRobust transformation with applications to structural equation modelling
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Self-citationIs formative measurement really measurement? Reply to Bollen (2007) and Bagozzi (2007).
Howell, R. D., Breivik, E., & Wilcox, J. B. (2007) · Psychological Methods · doi:10.1037/1082-989x.12.2.238 · Cited by 100
A Two-Stage Approach to Missing Data: Theory and Application to Auxiliary Variables
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Self-citationSqueezing interval change from ordinal panel data: Latent growth curves with ordinal outcomes.
Mehta, P. D., Neale, M. C., & Flay, B. R. (2004) · Psychological Methods · doi:10.1037/1082-989x.9.3.301 · Cited by 97
SEM of another flavour: Two new applications of the supplemented EM algorithm
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A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis
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Savalei, V., & Bentler, P. M. (2005) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1207/s15328007sem1202_1 · Cited by 91
Self-citationStructural Models and the Art of Approximation
McDonald, R. P. (2010) · Perspectives on Psychological Science · doi:10.1177/1745691610388766 · Cited by 90
On the Likelihood Ratio Test for the Number of Factors in Exploratory Factor Analysis
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Self-citationResidual Structures in Latent Growth Curve Modeling
Grimm, K. J., & Widaman, K. F. (2010) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2010.489006 · Cited by 90
A Second-Order Growth Mixture Model for Developmental Research
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A Semiparametric Approach to Modeling Nonlinear Relations Among Latent Variables
Bauer, D. J. (2005) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1207/s15328007sem1204_1 · Cited by 88
Yuan, K., & Bentler, P. M. (2002) · Psychometrika · doi:10.1007/bf02294845 · Cited by 88
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Can scientifically useful hypotheses be tested with correlations?
Bentler, P. M. (2007) · American Psychologist · doi:10.1037/0003-066x.62.8.772 · Cited by 86
Self-citationF Tests for Mean and Covariance Structure Analysis
Yuan, K., & Bentler, P. M. (1999) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986024003225 · Cited by 84
Self-citationAn EM Algorithm for Fitting Two-Level Structural Equation Models
Liang, J., & Bentler, P. M. (2004) · Psychometrika · doi:10.1007/bf02295842 · Cited by 83
Self-citationStructured Latent Curve Models for the Study of Change in Multivariate Repeated Measures.
Blozis, S. A. (2004) · Psychological Methods · doi:10.1037/1082-989x.9.3.334 · Cited by 83
Two Rules of Identification for Structural Equation Models
Bollen, K. A., & Davis, W. R. (2009) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705510903008261 · Cited by 83
Formative Measurement and Academic Research: In Search of Measurement Theory
Hardin, A. M., Chang, J., Fuller, M. A., & Torkzadeh, G. (2010) · Educational and Psychological Measurement · doi:10.1177/0013164410370208 · Cited by 81
Two simple approximations to the distributions of quadratic forms
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Self-citation17 Robust Procedures in Structural Equation Modeling
Yuan, K., & Bentler, P. M. (2007) · Handbook of computing and statistics with applications · doi:10.1016/b978-044452044-9/50020-3 · Cited by 78
Self-citationTests of Homogeneity of Means and Covariance Matrices for Multivariate Incomplete Data
Kim, K. H., & Bentler, P. M. (2002) · Psychometrika · doi:10.1007/bf02295134 · Cited by 78
Self-citationGold, M. S., Bentler, P. M., & Kim, K. H. (2003) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1207/s15328007sem1001_3 · Cited by 72
Self-citationStandard errors in covariance structure models: Asymptotics versus bootstrap
Yuan, K., & Hayashi, K. (2006) · British Journal of Mathematical and Statistical Psychology · doi:10.1348/000711005x85896 · Cited by 71
Structural Equation Modeling with Heavy Tailed Distributions
Yuan, K., Bentler, P. M., & Chan, W. (2004) · Psychometrika · doi:10.1007/bf02295644 · Cited by 70
Self-citationLocal Influence and Robust Procedures for Mediation Analysis
Zu, J., & Yuan, K. (2010) · Multivariate Behavioral Research · doi:10.1080/00273170903504695 · Cited by 70
Multilevel Factor Models for Ordinal Variables
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Robust Mean and Covariance Structure Analysis Through Iteratively Reweighted Least Squares
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Bias in factor score regression and a simple solution
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Metadata
- Authors
- Ullman, J. B., & Bentler, P. M.
- Venue
- Handbook of Psychology, Second Edition
- Publisher
- Wiley
- Published
- 2012-09-26
- Cited by
- 330
- References
- 261
- Language
- en
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