A new three-step method for using inverse propensity weighting with latent class analysis

DOI10.1007/S11634-021-00456-5OpenAlexW3186962680MaRDI QIDQ2089295

F. J. Clouth, Steffen Pauws, F. Mols, Jeroen K. Vermunt

Publication date: 6 October 2022

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11634-021-00456-5

zbMATH Keywords

causal inferencepropensity scoreaverage treatment effectlatent class analysisthree-step modelling

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Causal inference from observational studies (62D20)

Uses Software

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• Latent GOLD
• GitHub

Cites Work

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• Latent Variable Regression for Multiple Discrete Outcomes
• The role of the propensity score in estimating dose-response functions
• Finite mixture models
• Exploratory latent structure analysis using both identifiable and unidentifiable models
• Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
• A new look at the statistical model identification

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