Skip to main content
SpringerLink
Log in

Book ReviewStructural Equation Modeling: Applications using Mplus (Wang and Wang 2020)

  • Book Review
  • Published:
Psychometrika Aims and scope Submit manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  • Asparouhov, T., Hamaker, E. L., & Muthén, B. (2018). Dynamic structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 25, 359–388.

    Article  Google Scholar 

  • Bollen, K. A. (1989). Structural equations with latent variables. New York, NY: Wiley.

    Book  Google Scholar 

  • Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming. New York, NY: Routledge.

    Book  Google 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. (2019). Structural equation modeling. In G. R. Hancock, L. M. Stapleton, & R. O. Mueller (Eds.), The reviewer’s guide to quantitative methods in the social sciences (2nd ed., pp. 445–456). New York, NY: Routledge.

    Google Scholar 

  • Jak, S. (2015). Meta-analytic structural equation modelling. Germany: Springer.

    Book  Google 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.

    Article  Google 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.

    Article  Google 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 (4th ed.). 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 (2nd ed.). Charlotte, NC: Information Age Publishing.

    Google Scholar 

  • Muthén, B. (1978). Contributions to factor analysis of dichotomous variables. Psychometrika, 43, 551–560.

    Article  Google Scholar 

  • Muthén, B. O. (2001). Latent variable mixture modeling. In G. Marcoulides & R. Schumacker (Eds.), New developments and techniques in structural equation modeling (pp. 21–54). New York, NY: Psychology Press.

    Google Scholar 

  • Muthén, L. K., & Muthén, B. O. (1998-2017). Mplus user’s guide (8th ed.). Los Angeles, CA: Muthén & Muthén.

  • Newsom, J. T. (2015). Longitudinal structural equation modeling: A comprehensive introduction. New York, NY: Taylor & Francis.

    Book  Google Scholar 

  • Samejima, F. (1969). Estimation of a latent ability using a response pattern of graded scores. Psychometrika, 34, 1–97.

    Article  Google Scholar 

  • Samejima, F. (2016). Graded response models. In W. J. van der Linden (Ed.), Handbook of item response theory (Vol. 1, pp. 123–136). New York, NY: Chapman and Hall/CRC.

    Google Scholar 

  • Silva, B. C., Bosancianu, C. M., & Littvay, L. (2020). Multilevel structural equation modeling. Los Angeles, CA: SAGE Publications.

    Google Scholar 

  • Wang, J., & Wang, X. (2012). Structural equation modeling: Applications using Mplus (1st ed.). Hoboken, NJ: Wiley.

    Book  Google Scholar 

  • Wang, J., & Wang, X. (2020). Structural equation modeling: Applications using Mplus (2nd ed.). Hoboken, NJ: Wiley.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Human Development and Quantitative Methodology, University of Maryland, 3942 Campus Drive, College Park, MD, 20742-1115, USA

    Yi Feng & Jeffrey R. Harring

Authors
  1. Yi Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jeffrey R. Harring
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yi Feng.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Feng, Y., Harring, J.R. Book ReviewStructural Equation Modeling: Applications using Mplus (Wang and Wang 2020). Psychometrika 85, 526–530 (2020). https://doi.org/10.1007/s11336-020-09706-5

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11336-020-09706-5

Search

Navigation