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smcfcs: 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.

Version: 1.9.0
Depends: R (≥ 3.1.2)
Imports: MASS, survival, VGAM, stats, rlang, checkmate, abind, brglm2
Suggests: knitr, rmarkdown, mitools, ggplot2, kmi, flexsurv
Published: 2024-11-07
DOI: 10.32614/CRAN.package.smcfcs
Author: Jonathan Bartlett [aut, cre], Ruth Keogh [aut], Edouard F. Bonneville [aut], Claus Thorn Ekstrøm [ctb]
Maintainer: Jonathan Bartlett <jonathan.bartlett1 at lshtm.ac.uk>
License: GPL-3
URL: https://github.com/jwb133/smcfcs
NeedsCompilation: no
Materials: README
In views: MissingData
CRAN checks: smcfcs results

Documentation:

Reference manual: smcfcs.pdf
Vignettes: smcfcs (source, R code)
smcfcs_measerror (source, R code)

Downloads:

Package source: smcfcs_1.9.0.tar.gz
Windows binaries: r-devel: smcfcs_1.9.0.zip, r-release: smcfcs_1.9.0.zip, r-oldrel: smcfcs_1.9.0.zip
macOS binaries: r-release (arm64): smcfcs_1.9.0.tgz, r-oldrel (arm64): smcfcs_1.9.0.tgz, r-release (x86_64): smcfcs_1.9.0.tgz, r-oldrel (x86_64): smcfcs_1.9.0.tgz
Old sources: smcfcs archive

Reverse dependencies:

Reverse imports: bootImpute
Reverse suggests: Publish, riskRegression
Reverse enhances: mdmb

Linking:

Please use the canonical form https://CRAN.R-project.org/package=smcfcs to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.