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MICE

Multivariate Imputation by Chained Equations (MICE) is an iterative procedure for handling missing data in multivariate datasets. Introduced by Stef van Buuren and Karin Groothuis-Oudshoorn through the R package mice (2011), the algorithm fills each missing variable using a separate regression model conditioned on all other variables, cycling through variables repeatedly until the imputed values converge. The result is m completed datasets that are analysed separately and combined using Rubin's rules.

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Multivariate Imputation by Chained Equations (MICE)

Rekod kaedah taksonomik · process-pipeline / statistics

van Buuren, S., & Groothuis-Oudshoorn, K. (2011). mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1–67. · DOI 10.18637/jss.v045.i03

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Used in the same domainEM Algorithmmachine-suggested · Relational suggestion, not evidence.See alsoMatrix Completionmachine-suggested · Relational suggestion, not evidence.Same method familyMultiple Imputationmachine-suggested · Relational suggestion, not evidence.