A Systematic Review of and Reflection on the Applications of Factor Mixture Modeling (Poster 9)

• In Event: AERA Poster Session Fourteen
  In Poster Session: Systematic Review and Meta-Analysis SIG Poster Session

Abstract

Factor mixture modeling (FMM) incorporates both continuous latent variables and categorical latent variables in a single analytic model clustering items and observations simultaneously. After two decades since the introduction of FMM to the fields of educational and psychological research, it is the opportune time to review FMM applications to understand how it is utilized in the real-world research. We conduct a systematic review of 78 FMM applications and examine the common usage and practices of FMM. We identify challenges and issues that applied researchers would encounter in the practice of FMM and promote well-informed decision-making by providing practical suggestions. We also expand FMM beyond its typical use in the applied studies and discuss future directions in both methodology and applications.

Authors

• Eunsook Kim, University of South Florida
  Presenting Author

• Yan Wang, University of Massachusetts - Lowell
  Non-Presenting Author

• Hsien-Yuan Hsu, University of Massachusetts - Lowell
  Non-Presenting Author