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Mixture Modeling with MplusAutomation

Mixture Modeling with MplusAutomation

Welcome! This will be a collection of resources that will teach you how to apply mixture modeling using Mplus1 and MplusAutomation!2 These resources will serve as a comprehensive guide to understanding and applying mixture models using Mplus and its automation capabilities with MplusAutomation. Here, you will learn from start to finish how to apply a range of mixture modeling using Mplus with the MplusAutomation package.

Note: This book is a continuous work in progress. The code presented may be updated and/or expanded as research progresses. Please treat the material as a living document rather than a final product.

Stay in touch!

  • Please visit our website to learn more about the IMMERSE fellowship.

    • For all code and materials found in this Bookdown, see here.

  • Visit our GitHub account to access all the IMMERSE training materials.

  • Follow us on BlueSky and X to stay-up-to date on our fellowship!

Acknowledgements

The Institute of Mixture Modeling for Equity-Oriented Researchers, Scholars, and Educators (IMMERSE) is an IES funded training grant (R305B220021) to support education scholars in integrating mixture modeling into their research.

How to reference this website: Institute of Mixture Modeling for Equity-Oriented Researchers, Scholars, and Educators (2025). IMMERSE Online Resources (IES No. 305B220021). Institute of Education Sciences. https://mixture-modeling.netlify.app/

Authors & Contributors

This resource was developed by the IMMERSE team:

  • Dina Arch, PhD, Postdoctoral Scholar

  • Karen Nylund-Gibson, PhD, Principal Investigator

  • Marsha Ing, PhD, Co-Principal Investigator

  • Katherine Masyn, PhD, Co-Principal Investigator

Additional code contributors:

  • Adam Garber, PhD

  • Delwin Carter, PhD

  • Yidi Zhang, MA

We also thank all the IMMERSE fellows who provided feedback during the development of these materials.