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A two-step estimator for multilevel latent class analysis with covariates

Di Mari, Roberto, Bakk, Zsuzsa, Oser, Jennifer and Kuha, Jouni ORCID: 0000-0002-1156-8465 (2023) A two-step estimator for multilevel latent class analysis with covariates. Psychometrika, 88 (4). 1144 - 1170. ISSN 0033-3123

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Identification Number: 10.1007/s11336-023-09929-2

Abstract

We propose a two-step estimator for multilevel latent class analysis (LCA) with covariates. The measurement model for observed items is estimated in its first step, and in the second step covariates are added in the model, keeping the measurement model parameters fixed. We discuss model identification, and derive an Expectation Maximization algorithm for efficient implementation of the estimator. By means of an extensive simulation study we show that (1) this approach performs similarly to existing stepwise estimators for multilevel LCA but with much reduced computing time, and (2) it yields approximately unbiased parameter estimates with a negligible loss of efficiency compared to the one-step estimator. The proposal is illustrated with a cross-national analysis of predictors of citizenship norms.

Item Type: Article
Official URL: https://www.springer.com/journal/11336
Additional Information: © 2023 The Author(s)
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
Date Deposited: 16 Aug 2023 09:09
Last Modified: 09 Jun 2024 20:45
URI: http://eprints.lse.ac.uk/id/eprint/119994

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