Two-stage Multilevel Latent Class Analysis with Covariates in the Presence of Direct Effects

Zsuzsa Bakk, Roberto Di Mari, Jennifer Oser, Jouni Kuha

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In this article, we present a two-stage estimation approach applied to multilevel latent class analysis (LCA) with covariates. We separate the estimation of the measurement and structural model. This makes the extension of the structural model computationally efficient. We investigate the robustness against misspecifications of the proposed two-stage and the classical one-stage approach for models where a direct effect exists between indicators of the LC model and covariate, and the direct effect is ignored.

Original languageEnglish
Pages (from-to)267-277
Number of pages11
JournalStructural Equation Modeling
Volume29
Issue number2
DOIs
StatePublished - 1 Jan 2022

Keywords

  • Multilevel latent class analysis
  • covariates
  • direct effect
  • two-stage estimation

ASJC Scopus subject areas

  • General Decision Sciences
  • Modeling and Simulation
  • Sociology and Political Science
  • Economics, Econometrics and Finance (all)

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