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StackImpute: Tools for Analysis of Stacked Multiple Imputations

Provides methods for inference using stacked multiple imputations augmented with weights. The vignette provides example R code for implementation in general multiple imputation settings. For additional details about the estimation algorithm, we refer the reader to Beesley, Lauren J and Taylor, Jeremy M G (2020) “A stacked approach for chained equations multiple imputation incorporating the substantive model” <doi:10.1111/biom.13372>, and Beesley, Lauren J and Taylor, Jeremy M G (2021) “Accounting for not-at-random missingness through imputation stacking” <doi:10.48550/arXiv.2101.07954>.

Version:0.1.0
Depends:R (≥ 3.6.0)
Imports:sandwich,zoo,mice,dplyr,MASS,magrittr,boot
Suggests:knitr,rmarkdown
Published:2021-09-10
DOI:10.32614/CRAN.package.StackImpute
Author:Lauren Beesley [aut], Mike Kleinsasser [cre]
Maintainer:Mike Kleinsasser <mkleinsa at umich.edu>
License:GPL-2
NeedsCompilation:no
Materials:README
CRAN checks:StackImpute results

Documentation:

Reference manual:StackImpute.html ,StackImpute.pdf
Vignettes:UsingStackImpute (source,R code)

Downloads:

Package source: StackImpute_0.1.0.tar.gz
Windows binaries: r-devel:StackImpute_0.1.0.zip, r-release:StackImpute_0.1.0.zip, r-oldrel:StackImpute_0.1.0.zip
macOS binaries: r-release (arm64):StackImpute_0.1.0.tgz, r-oldrel (arm64):StackImpute_0.1.0.tgz, r-release (x86_64):StackImpute_0.1.0.tgz, r-oldrel (x86_64):StackImpute_0.1.0.tgz

Reverse dependencies:

Reverse imports:SynDI

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=StackImputeto link to this page.


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