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 languageAmerican English
Pages (from-to)592-603
Number of pages12
JournalStructural Equation Modeling
Volume31
Issue number4
DOIs
StatePublished - 1 Jan 2024

Keywords

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

All Science Journal Classification (ASJC) codes

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

Fingerprint

Dive into the research topics of 'Bias-Adjusted Three-Step Multilevel Latent Class Modeling with Covariates'. Together they form a unique fingerprint.

Cite this