Project Activities
The training is intended for researchers who have some background in statistics, access to data, and potential research questions that could be addressed using a mixture model.
The trainers will recruit 2 cohorts of 12 participants to engage in a year long, intensive training program involving online synchronous and asynchronous mixture modeling training, a 3-day in-person training and community building event, and 1-year of mentoring and ongoing professional learning opportunities. Training will cover multiple topics relevant for the systematic, purposeful, and principled application of mixture modeling to real data through a combination of lectures, structured cooperative learning activities, and hands-on lab sessions.
A second focus of the program is the development and dissemination of an extensive set of freely available, online methodological training materials that highlight the utility of mixture modeling and provide specific support to encourages the best practice of mixture modeling. These materials include online videos on data analysis topics and tasks related to the application mixture modeling, annotated output files for Mplus and MplusAutomation, and resources for running models and creating related graphical results and figures in mixture modeling.
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
Publications:
Cosso, J., & Melzi, G. (2025). Numeracy engagement patterns of US Latine families. Journal of Cognition and Development, 26(1), 158-173.
Denson, N., Arch, D. A. N., Garber, A. C., Chan, M. K., Carter, D. B., & Nylund-Gibson, K. (2022). A latent class analysis of students’ openness to learning from diverse others. Journal of Diversity in Higher Education.
Winkler, C. E., & Wofford, A. M. (2024). Trends and Motivations in Critical Quantitative Educational Research: A Multimethod Examination Across Higher Education Scholarship and Author Perspectives. Research in Higher Education, 65(7), 1368-1394.
Yun, H. Y. (2025). Rejection or Tolerance of Bullies: The Roles of Descriptive, Injunctive, and Popularity Norms. Social Development, 34(3), e12806.
Yun, H. Y., & Espelage, D. (2024). Self-ratings and peer-ratings of bullying perpetrators: Intrapersonal and interpersonal factors that differentiate bully subgroups. Journal of School Psychology, 106, 101358.
Zajic, M. C., Gudknecht, J., & McIntyre, N. S. (2025). Characterizing the Special Education Goals of Autistic Students: Latent Class Analysis With Demographic and Developmental Covariates. Exceptional Children, 00144029251331861.
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.
