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Relating latent class membership to external variables: an overview

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  • Bakk, Zsuzsa
  • Kuha, Jouni

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.

Suggested Citation

  • Bakk, Zsuzsa & Kuha, Jouni, 2020. "Relating latent class membership to external variables: an overview," LSE Research Online Documents on Economics 107564, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:107564
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    File URL: http://eprints.lse.ac.uk/107564/
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    References listed on IDEAS

    as
    1. Bakk, Zsuzsa & Kuha, Jouni, 2018. "Two-step estimation of models between latent classes and external variables," LSE Research Online Documents on Economics 85161, London School of Economics and Political Science, LSE Library.
    2. Bakk, Zsuzsa & Oberski, Daniel L. & Vermunt, Jeroen K., 2014. "Relating Latent Class Assignments to External Variables: Standard Errors for Correct Inference," Political Analysis, Cambridge University Press, vol. 22(4), pages 520-540.
    3. Vermunt, Jeroen K., 2010. "Latent Class Modeling with Covariates: Two Improved Three-Step Approaches," Political Analysis, Cambridge University Press, vol. 18(4), pages 450-469.
    4. Zsuzsa Bakk & Jouni Kuha, 2018. "Two-Step Estimation of Models Between Latent Classes and External Variables," Psychometrika, Springer;The Psychometric Society, vol. 83(4), pages 871-892, December.
    5. Bolck, Annabel & Croon, Marcel & Hagenaars, Jacques, 2004. "Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators," Political Analysis, Cambridge University Press, vol. 12(1), pages 3-27, January.
    6. Zhu, Yajing & Steele, Fiona & Moustaki, Irini, 2017. "A general 3-step maximum likelihood approach to estimate the effects of multiple latent categorical variables on a distal outcome," LSE Research Online Documents on Economics 81850, London School of Economics and Political Science, LSE Library.
    7. Qian-Li Xue & Karen Bandeen-Roche, 2002. "Combining Complete Multivariate Outcomes with Incomplete Covariate Information: A Latent Class Approach," Biometrics, The International Biometric Society, vol. 58(1), pages 110-120, March.
    8. Mustillo, Thomas J., 2009. "Modeling New Party Performance: A Conceptual and Methodological Approach for Volatile Party Systems," Political Analysis, Cambridge University Press, vol. 17(3), pages 311-332, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    covariates; distal outcome; latent class analysis; three-step estimation; two-step estimation;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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