MICE: Multivariate Imputation by Chained Equations in R
Year: 2010
Type: article
Abstract: Multivariate Imputation by Chained Equations (MICE) is the name of software for \nimputing incomplete multivariate data by Fully Conditional Speci cation (FCS). MICE \nV1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. MICE \nV1.0 introduced predictor selection, passive imputation and automatic pooling. This \narticle presents MICE V2.0, which extends the functionality of MICE V1.0 in several ways. \nIn MICE V2.0, the analysis of imputed data is made completely general, whereas the range \nof models under which pooling works is substantially extended. MICE V2.0 adds new \nfunctionality for imputing multilevel data, automatic predictor selection, data handling, \npost-processing imputed values, specialized pooling and model selection. Imputation of \ncategorical data is improved in order to bypass problems caused by perfect prediction. \nSpecial attention to transformations, sum scores, indices and interactions using passive \nimputation, and to the proper setup of the predictor matrix. MICE V2.0 is freely available \nfrom CRAN as an R package mice. This article provides a hands-on, stepwise approach \nto using mice for solving incomplete data problems in real data.
Authors: Buuren, S. van, Groothuis-Oudshoorn, K.
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7011406682