Bias-Adjusted Three-Step Multilevel Latent Class Modeling with Covariates

Johan Lyrvall, Zsuzsa Bakk, Jennifer Oser, Roberto Di Mari

Research output: Contribution to journalArticlepeer-review

Abstract

We present a bias-adjusted three-step estimation approach for multilevel latent class models (LC) with covariates. The proposed approach involves (1) fitting a single-level measurement model while ignoring the multilevel structure, (2) assigning units to latent classes, and (3) fitting the multilevel model with the covariates while controlling for measurement error introduced in the second step. Simulation studies and an empirical example show that the three-step method is a legitimate modeling option compared to the existing one-step and two-step methods.

Original languageEnglish
JournalStructural Equation Modeling
DOIs
StateAccepted/In press - 1 Jan 2024

Keywords

  • Bias-adjusted three-step estimation
  • covariates
  • latent class analysis
  • multilevel

ASJC Scopus subject areas

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

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