A longitudinal transition imputation model for categorical data applied to a large registry dataset

DOI10.1002/sim.9919zbMATH Open1540.62168MaRDI QIDQ6560542

Arne Janssens, Vahid Nassiri, Geert Verbeke, Geert Molenberghs, Pavlos Mamouris, Bert Vaes

Publication date: 23 June 2024

Published in: (Search for Journal in Brave)

zbMATH Keywords

multiple imputationtransition probabilitiesregistry datasmoking outcome

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Title not available (Why is that?)
• Avoiding bias due to perfect prediction in multiple imputation of incomplete categorical variables
• Models for discrete longitudinal data.
• Missing data
• Fully conditional specification in multivariate imputation
• Markov Chains
• Flexible Imputation of Missing Data, Second Edition
• Iterative Multiple Imputation: A Framework to Determine the Number of Imputed Datasets
• A comparison of multiple-imputation methods for handling missing data in repeated measurements observational studies

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