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. 2021 May;74(2):340-362.
doi: 10.1111/bmsp.12227. Epub 2020 Nov 16.

Relating latent class membership to external variables: An overview

Zsuzsa Bakk  1 , Jouni Kuha  2
Affiliations

Relating latent class membership to external variables: An overview

Zsuzsa Bakk et al. Br J Math Stat Psychol. 2021 May.

Abstract

In this article we provide an overview of existing approaches for relating latent class membership to external variables of interest. We extend on the work of Nylund-Gibson et al. (Structural Equation Modeling: A Multidisciplinary Journal, 2019, 26, 967), who summarize models with distal outcomes by providing an overview of most recommended modeling options for models with covariates and larger models with multiple latent variables as well. We exemplify the modeling approaches using data from the General Social Survey for a model with a distal outcome where underlying model assumptions are violated, and a model with multiple latent variables. We discuss software availability and provide example syntax for the real data examples in Latent GOLD.

Keywords: covariates; distal outcome; latent class analysis; three-step estimation; two-step estimation.

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Conflict of interest statement

All authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The basic latent class model (measurement model) and the one‐step model including covariates Zp and distal outcomes Zo.
Figure 2
Figure 2
The LTB approach.
Figure 3
Figure 3
The ‘classical’ three‐step approach.
Figure 4
Figure 4
The bias‐adjusted three‐step approaches.
Figure 5
Figure 5
The second step of the two step approaches: the model including a covariate and the model including a distal outcome.
See this image and copyright information in PMC

References

    1. Asparouhov, T. , & Muthèn, B. (2014a). Auxiliary variables in mixture modeling: Three‐step approaches using mplus. Structural Equation Modeling: A Multidisciplinary Journal, 21, 329–341. 10.1080/10705511.2014.915181 - DOI
    1. Asparouhov, T. , & Muthén, B. (2014b). Auxiliary variables in mixture modeling: Using the bch method in Mplus to estimate a distal outcome model on an arbitrary secondary model. Retrieved from http://www.statmodel.com/examples/webnotes/webnote21.pdf
    1. Bakk, Z. , & Kuha, J. (2018). Two‐step estimation of models between latent classes and external variables. Psychometrika, 83, 871–892. 10.1007/s11336-017-9592-7 - DOI - PubMed
    1. Bakk, Z. , Oberski, D. , & Vermunt, J. (2014). Relating latent class assignments to external variables: Standard errors for correct inference. Political Analysis, 22, 520–540. 10.1093/pan/mpu003 - DOI
    1. Bakk, Z. , Oberski, D. L. , & Vermunt, J. K. (2016). Relating latent class membership to continuous distal outcomes: Improving the LTB approach and a modified three‐step implementation. Structural Equation Modeling: A Multidisciplinary Journal, 23, 278–289. 10.1080/10705511.2015.1049698 - DOI