Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013 Oct 1;20(4):10.1080/10705511.2013.824786.
doi: 10.1080/10705511.2013.824786.

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

Shaunna L Clark  1 , Bengt Muthén, Jaakko Kaprio, Brian M D'Onofrio, Richard Viken, Richard J Rose
Affiliations

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

Shaunna L Clark et al. Struct Equ Modeling. .

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.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Model Diagrams. (a) Latent Class Analysis, (b) Factor Analysis, (c) Generalized Factor Mixture Model, (d) FMM-1, (e) FMM-2, (f) FMM-3, (g) FMM-4.
Figure 1
Figure 1
Model Diagrams. (a) Latent Class Analysis, (b) Factor Analysis, (c) Generalized Factor Mixture Model, (d) FMM-1, (e) FMM-2, (f) FMM-3, (g) FMM-4.
Figure 2
Figure 2
Example Factor Distribution Plots. (a) FMM-1with four classes, (b) FMM-2 with two classes.
Figure 3
Figure 3
Outline of FMM Model Building Strategy.
Figure 4
Figure 4
Conduct Disorder Example: Three-Class Latent Class Analysis Profile Plot.
Figure 5
Figure 5
Conduct Disorder Example: Two-Class, One-Factor FMM-2 Profile Plot. SD = standard deviation.
Figure 6
Figure 6
Conduct Disorder Example: Two-Class, One-Factor FMM-2 Factor Distribution Plot.
See this image and copyright information in PMC

References

    1. Bauer DJ, Curran PJ. Distributional assumptions of growth mixture models: Implications for overextraction of latent trajectory classes. Psychological Methods. 2003a;8:338–363. - PubMed
    1. Bauer DJ, Curran PJ. Over-extracting latent trajectory classes: Much ado about nothing? Psychological Methods. 2003b;8:384–393. - PubMed
    1. Bauer DJ, Curran PJ. The integration of continuous and discrete latent variable models: Potential problems and promising opportunities. Psychological Methods. 2004;9:3–29. - PubMed
    1. Clark SL. Doctoral dissertation. Los Angeles: University of California; 2010. Mixture modeling with behavioral data. ( http://www.statmodel.com/download/Dissertation_v1.pdf)
    1. Flora DB, Curran PJ. An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods. 2004;9(4):466–491. - PMC - PubMed

LinkOut - more resources