Clustering with missing and left‐censored data: A simulation study comparing multiple‐imputation‐based procedures

DOI10.1002/bimj.201900366zbMath1523.62113OpenAlexW3039859484WikidataQ97087139 ScholiaQ97087139MaRDI QIDQ6071305

Emmanuel Curis, Unnamed Author, Unnamed Author, Matthieu Resche-Rigon, Sylvie Chevret

Publication date: 23 November 2023

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.201900366

zbMATH Keywords

clusteringmissing datamultiple imputationbreast cancerconsensusleft-censored data

Mathematics Subject Classification ID

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

Related Items (1)

Clustering with missing data: which equivalent for Rubin's rules?

Cites Work

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• 10.1162/153244303321897735
• Clustering multiply imputed multivariate high‐dimensional longitudinal profiles
• k-POD: A Method for k-Means Clustering of Missing Data

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