Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification

Implements multiple imputation of missing covariates by Substantive Model Compatible Fully Conditional Specification. This is a modification of the popular FCS/chained equations multiple imputation approach, and allows imputation of missing covariate values from models which are compatible with the user specified substantive model.


smcfcs is an R package implementing Substantive Model Compatibly Fully Conditional Specification Multiple Imputation. Examples and further details are given in the package documentation and vignette.

To install the latest GitHub development version, run:

install.packages("devtools")

devtools::install_github("jwb133/smcfcs")

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Reference manual

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install.packages("smcfcs")

1.5.0 by Jonathan Bartlett, 12 days ago


https://github.com/jwb133/smcfcs


Browse source code at https://github.com/cran/smcfcs


Authors: Jonathan Bartlett [aut, cre] , Ruth Keogh [aut] , Claus Thorn Ekstrøm [ctb] , Edouard F. Bonneville [ctb]


Documentation:   PDF Manual  


Task views: Missing Data


GPL-3 license


Imports MASS, survival, VGAM, stats, rlang

Suggests knitr, rmarkdown, mitools, ggplot2


Imported by bootImpute.

Suggested by Publish, riskRegression.

Enhanced by mdmb.


See at CRAN