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Structural Equation Modeling: Applications using Mplus (Wang and Wang 2020)

Published online by Cambridge University Press:  01 January 2025

Yi Feng Open the ORCID record for Yi Feng [Opens in a new window]  and
Jeffrey R. Harring
Yi Feng*
Affiliation:
University of Maryland
Jeffrey R. Harring
Affiliation:
University of Maryland
*
Correspondence should be made to Yi Feng, Department of Human Development and Quantitative Methodology, University of Maryland, 3942 Campus Drive, College Park, MD 20742-1115, USA. Email: yifeng94@umd.edu
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Information

Type
Book Review
Information
Psychometrika , Volume 85 , Issue 2 , June 2020 , pp. 526 - 530
Copyright
Copyright © 2020 The Psychometric Society

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References

Asparouhov, T., Hamaker, E. L., & Muthén, B. (2018). Dynamic structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 25, 359– 388. CrossRefGoogle Scholar
Bollen, K. A. (1989). Structural equations with latent variables. New York, NY: Wiley. CrossRefGoogle Scholar
Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming. New York, NY: Routledge. CrossRefGoogle Scholar
Grimm, K. J., Ram, N., & Estabrook, R. (2016). Growth modeling: Structural equation and multilevel modeling approaches. New York, NY: Guilford Publications. Google Scholar
Hancock, G. R., & Mueller, R. O. Hancock, G. R., Stapleton, L. M., & Mueller, R. O. (2019). Structural equation modeling. The reviewer’s guide to quantitative methods in the social sciences 2. New York, NY: Routledge. 445– 456. Google Scholar
Jak, S. (2015). Meta-analytic structural equation modelling. Germany: Springer. CrossRefGoogle Scholar
Jedidi, K., Jagpal, H. S., & DeSarbo, W. S. (1997). Finite-mixture structural equation models for response-based segmentation and unobserved heterogeneity. Marketing Science, 16, 39– 59. CrossRefGoogle Scholar
Kaplan, D., Elliott, P. R. (1997). A didactic example of multilevel structural equation modeling applicable to the study of organizations. Structural Equation Modeling: A Multidisciplinary Journal, 4, 1– 24. CrossRefGoogle Scholar
Kelloway, E. K. (2014). Using Mplus for structural equation modeling: A researcher’s guide. Thousand Oaks: Sage Publications. Google Scholar
Kline, R. B. (2016). Principles and practice of structural equation modeling 4. New York, NY: Guilford Publications. Google Scholar
Lord, F. M. (1980). Applications of item response theory to practical testing problems. New York, NY: Routledge. Google Scholar
Mueller, R. O., & Hancock, G. R. (2013). Structural equation modeling: A second course 2. Charlotte, NC: Information Age Publishing. Google Scholar
Muthén, B. (1978). Contributions to factor analysis of dichotomous variables. Psychometrika, 43, 551– 560. CrossRefGoogle Scholar
Muthén, B. O. Marcoulides, G.& Schumacker, R. Latent variable mixture modeling. New developments and techniques in structural equation modeling, (2001). New York, NY: Psychology Press. 21– 54. Google Scholar
Muthén, L. K., & Muthén, B. O. (1998-2017). Mplus user’s guide (8th ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
Newsom, J. T. (2015). Longitudinal structural equation modeling: A comprehensive introduction. New York, NY: Taylor & Francis. CrossRefGoogle Scholar
Samejima, F. (1969). Estimation of a latent ability using a response pattern of graded scores. Psychometrika, 34, 1– 97. CrossRefGoogle Scholar
Samejima, F. van der Linden, W. J. (2016). Graded response models. Handbook of item response theory, New York, NY: Chapman and Hall/CRC. 123– 136. Google Scholar
Silva, B. C., Bosancianu, C. M., & Littvay, L. (2020). Multilevel structural equation modeling. Los Angeles, CA: SAGE Publications. CrossRefGoogle Scholar
Wang, J., & Wang, X. (2012). Structural equation modeling: Applications using Mplus 1. Hoboken, NJ: Wiley. CrossRefGoogle Scholar
Wang, J., & Wang, X. (2020). Structural equation modeling: Applications using Mplus 2. Hoboken, NJ: Wiley. Google Scholar