Models and Strategies for Factor Mixture Analysis: An Example Concerning the Structure Underlying Psychological Disorders

  • Clark S
  • Muthén B
  • Kaprio J
 et al. 
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Abstract

The factor mixture model (FMM) uses a hybrid of both categorical and continuous latent variables. The FMM is a good model for the underlying structure of psychopathology because the use of both categorical and continuous latent variables allows the structure to be simultaneously categorical and dimensional. This is useful because both diagnostic class membership and the range of severity within and across diagnostic classes can be modeled concurrently. While the conceptualization of the FMM has been explained in the literature, the use of the FMM is still not prevalent. One reason is that there is little research about how such models should be applied in practice and, once a well fitting model is obtained, how it should be interpreted. In this paper, the FMM will be explored by studying a real data example on conduct disorder. By exploring this example, this paper aims to explain the different formulations of the FMM, the various steps in building a FMM, as well as how to decide between a FMM and alternative models.

Author-supplied keywords

  • factor mixture model
  • finite mixture model
  • latent class analysis

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Authors

  • Shaunna L. Clark

  • Bengt Muthén

  • Jaakko Kaprio

  • Brian M. D'Onofrio

  • Richard Viken

  • Richard J. Rose

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