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” <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
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.pdf
Vignettes: UsingStackImpute

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

Reverse dependencies:

Reverse imports: SynDI

Linking:

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