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 form https://CRAN.R-project.org/package=StackImpute to link to this page.