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

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
JournalStructural Equation Modeling
DOIs
StateAccepted/In press - 1 Jan 2021

Keywords

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

ASJC Scopus subject areas

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

Fingerprint

Dive into the research topics of 'Two-stage Multilevel Latent Class Analysis with Covariates in the Presence of Direct Effects'. Together they form a unique fingerprint.

Cite this