STEP3: Stata module to relate latent class membership to external variables

Giovanbattista Califano

Statistical Software Components from Boston College Department of Economics

Abstract: step3 performs two bias-adjusted three-step methods to relate latent class membership to external variables: Maximum Likelihood (ML; Vermunt, 2010) and Bolck-Croon-Hagenaars (BCH; Bolck et al., 2004). The external variables can be either covariates (predictors of class membership) or distal outcomes (predicted by class membership). The command adjusts for misclassification errors that arise in three-step approaches when observations are assigned to classes based on posterior probabilities from an initial latent class model. The first step (estimating the latent class model and predicting posterior probabilities) must be done separately (e.g., with gsem or fmm). step3 uses these predicted probabilities to construct a classification error matrix and fits the structural model via ML or BCH correction.

Language: Stata
Requires: Stata version 15.1
Keywords: latent class analysis; stepwise procedure (search for similar items in EconPapers)
Date: 2023-02-14, Revised 2025-10-11
Note: This module should be installed from within Stata by typing "ssc install step3". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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http://fmwww.bc.edu/repec/bocode/s/step3.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/s/step3.sthlp help file (text/plain)

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