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Micro–macro multilevel latent class models with multiple discrete individual-level variables

Author

Listed:
  • Margot Bennink

    (Tilburg University)

  • Marcel A. Croon

    (Tilburg University)

  • Brigitte Kroon

    (Tilburg University)

  • Jeroen K. Vermunt

    (Tilburg University)

Abstract

An existing micro–macro method for a single individual-level variable is extended to the multivariate situation by presenting two multilevel latent class models in which multiple discrete individual-level variables are used to explain a group-level outcome. As in the univariate case, the individual-level data are summarized at the group-level by constructing a discrete latent variable at the group level and this group-level latent variable is used as a predictor for the group-level outcome. In the first extension, that is referred to as the Direct model, the multiple individual-level variables are directly used as indicators for the group-level latent variable. In the second extension, referred to as the Indirect model, the multiple individual-level variables are used to construct an individual-level latent variable that is used as an indicator for the group-level latent variable. This implies that the individual-level variables are used indirectly at the group-level. The within- and between components of the (co)varn the individual-level variables are independent in the Direct model, but dependent in the Indirect model. Both models are discussed and illustrated with an empirical data example.

Suggested Citation

  • Margot Bennink & Marcel A. Croon & Brigitte Kroon & Jeroen K. Vermunt, 2016. "Micro–macro multilevel latent class models with multiple discrete individual-level variables," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(2), pages 139-154, June.
    • Handle: RePEc:spr:advdac:v:10:y:2016:i:2:d:10.1007_s11634-016-0234-1
    DOI: 10.1007/s11634-016-0234-1
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    References listed on IDEAS

    as
    1. 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.
    2. David E. Guest & Riccardo Peccei, 2001. "Partnership at Work: Mutuality and the Balance of Advantage," British Journal of Industrial Relations, London School of Economics, vol. 39(2), pages 207-236, June.
    3. 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.
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