Skip to main content
SpringerLink
Log in

Concepts and Applications of Multivariate Multilevel (MVML) Analysis and Multilevel Structural Equation Modeling (MLSEM)

  • Chapter
  • First Online:
Methodology for Multilevel Modeling in Educational Research

  • 956 Accesses

Abstract

Multilevel or hierarchical models (MLM, HLM) are widely used in analyzing the nested data in educational research over the past decades. The current trend in the research includes systematical thinking of the relationships in education (e.g., ecosystem model of human development) and continuous measurement on individual’s performance (e.g., formative math assessment). These research focuses require that traditional analyses—structural equation modeling and multivariate analysis, work together with the MLM/HLM. This chapter will introduce two state-of-the-art techniques, which refer to multivariate multilevel (MVML) analysis and multilevel structural equation modeling (MLSEM). First, we will present the concepts of the MVML and MLSEM, emphasizing the ideas rather than algebra, to establish a theoretical and methodological foundation of the models. The MVML analysis allows for an analysis of multiple outcomes simultaneously, which can decompose the residual variances and covariances among outcome indicators into different levels. The MLSEM provides more appropriate estimates compared with SEM by considering the intra-class correlations. Then, we will discuss how the models can be applied to educational research. We expect both readers and researchers can find a more extended coverage of basic and advanced modeling techniques and get an enriched understanding of the value of MLM for future studies.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • American Psychological Association. (2020). Publication manual of the APA (7th ed.). Author.

    Google Scholar 

  • Bellens, K., Van Damme, J., Van Den Noortgate, W., Wendt, H., & Nilsen, T. (2019). Instructional quality: Catalyst or pitfall in educational systems’ aim for high achievement and equity? An answer based on multilevel SEM analyses of TIMSS 2015 data in Flanders (Belgium), Germany, and Norway. Large-Scale Assessments in Education, 7(1), 1–27.

    Article  Google Scholar 

  • Bliese, P. D. (1998). Group size, ICC values, and group-level correlations: A simulation. Organizational Research Methods, 1(4), 355–373.

    Article  Google Scholar 

  • Dedrick, R. F., Ferron, J. M., Hess, M. R., Hogarty, K. Y., Kromrey, J. D., Lang, T. R., Niles, J. D., & Lee, R. S. (2009). Multilevel modeling: A review of methodological issues and applications. Review of Educational Research, 79(1), 69–102.

    Google Scholar 

  • Desimone, L. M. (2009). Improving impact studies of teachers’ professional development: Toward better conceptualizations and measures. Educational Researcher, 38(3), 181–199.

    Article  Google Scholar 

  • Hall, J., & Malmberg, L. (2020). The contribution of multilevel structural equation modelling to contemporary trends in educational research. International Journal of Research & Method in Education, 43(4), 339–347. https://doi.org/10.1080/1743727X.2020.1796066

    Article  Google Scholar 

  • Hox, J. (2002). Multilevel analysis: Techniques and applications. Lawrence Erlbaum.

    Book  Google Scholar 

  • Hox, J. J., Moerbeek, M., & Van de Schoot, R. (2017). Multilevel analysis: Techniques and applications. Routledge.

    Google Scholar 

  • Kiwanuka, H. N., Van Damme, J., Van Den Noortgate, W., Anumendem, D. N., Vanlaar, G., Reynolds, C., & Namusisi, S. (2017). How do student and classroom characteristics affect attitude toward mathematics? A multivariate multilevel analysis. School Effectiveness and School Improvement, 28(1), 1–21. https://doi.org/10.1080/09243453.2016.1201123

    Article  Google Scholar 

  • Lee, J., Kim, T., & Su, M. (2021). Reassessing school effectiveness: Multi-objective value-added measures (MOVAM) of academic and socioemotional learning. Studies in Educational Evaluation, 68, 100972. https://doi.org/10.1016/j.stueduc.2020.100972

    Article  Google Scholar 

  • Lee, J., Shapiro, V. B., Kim, B. K. E., & Yoo, J. P. (2018). Multilevel structural equation modeling for social work researchers: An introduction and application to healthy youth development. Journal of the Society for Social Work and Research, 9(4), 689–719. https://doi.org/10.1086/701526

    Article  Google Scholar 

  • MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51, 201–226.

    Article  Google Scholar 

  • MuthĂ©n, L. K., & MuthĂ©n, B. O. (2012). Mplus version 7.0 [computer software]. Retrieved from https://www.statmodel.com/index.shtml

  • Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods, 15(3), 209–233.

    Google Scholar 

  • Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. Sage.

    Google Scholar 

  • Schneider, B., White, S. S., & Paul, M. C. (1998). Linking service climate and corner perceptions of service quality: Test of a causal model. Journal of Applied Psychology, 83, 150–163.

    Article  Google Scholar 

  • Schreiber, J. B., & Griffin, B. W. (2004). Review of multilevel modeling and multilevel studies in The Journal of Educational Research (1992–2002). The Journal of Educational Research, 98, 24–33.

    Article  Google Scholar 

  • Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling. Sage.

    Google Scholar 

  • Su, M. (2021). The mediation effect of student engagement on the relationship between school climate, socioemotional well-being, and academic achievement: A cross-cultural comparative study of China, Korea, Finland, and the U.S. (Order No. 28645024). Available from ProQuest Dissertations & Theses Global. (2580988311). https://www.proquest.com/dissertations-theses/mediation-effect-student-engagement-on/docview/2580988311/se-2?accountid=14169

  • Su, M., & Lee, J. (2021, April). Whole-child education: China, Korea, Finland, and U.S. Students’ Academic Achievement and Socio-Emotional Well-Being. Paper presented at the 2021 annual meeting of American Educational Research Association (AERA), virtual conference.

    Google Scholar 

  • Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5, pp. 481–498). Pearson.

    Google Scholar 

  • Van de Schoot, R., Lugtig, P., & Hox, J. (2012). A checklist for testing measurement invariance. European Journal of Developmental Psychology, 9(4), 486–492.

    Article  Google Scholar 

  • Woltman, H., Feldstain, A., MacKay, J. C., & Rocchi, M. (2012). An introduction to hierarchical linear modeling. Tutorials in Quantitative Methods for Psychology, 8(1), 52–69.

    Google Scholar 

  • Yang, Y., Liu, X., & Gardella, J. A., Jr. (2020). Effects of a professional development program on science teacher knowledge and practice, and student understanding of interdisciplinary science concepts. Journal of Research in Science Teaching, 57(7), 1028–1057.

    Article  Google Scholar 

  • Yang, Y., Liu, X., & Gardella, J. (2018). Impact of professional development on teacher knowledge, practice and student understanding of science in an interdisciplinary science and engineering partnership. Journal of Science Teacher Education, 29(4), 263–282.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Beijing Normal University, Zhuhai, China

    Yang Yang

  2. University at Buffalo, Buffalo, NY, USA

    Mengchen Su & Ren Liu

Authors
  1. Yang Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mengchen Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ren Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yang Yang .

Editor information

Editors and Affiliations

  1. Curtin University, Bentley, WA, Australia

    Myint Swe Khine

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Yang, Y., Su, M., Liu, R. (2022). Concepts and Applications of Multivariate Multilevel (MVML) Analysis and Multilevel Structural Equation Modeling (MLSEM). In: Khine, M.S. (eds) Methodology for Multilevel Modeling in Educational Research. Springer, Singapore. https://doi.org/10.1007/978-981-16-9142-3_4

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-9142-3_4

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-9141-6

  • Online ISBN: 978-981-16-9142-3

  • eBook Packages: EducationEducation (R0)

Publish with us

Policies and ethics

Search

Navigation