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Boxplots adapted to the happenstance of missing observations where drop-out probabilities can be given by the practitioner or modelled using auxiliary covariates. The paper of "Zhang, Z., Chen, Z., Troendle, J. F. and Zhang, J.(2012) <doi:10.1111/j.1541-0420.2011.01712.x>", proposes estimators of marginal quantiles based on the Inverse Probability Weighting method.
Version: | 0.1.2 |
Imports: | isotone |
Suggests: | mice, knitr, rmarkdown |
Published: | 2023-10-21 |
DOI: | 10.32614/CRAN.package.IPWboxplot |
Author: | Ana Maria Bianco [aut], Graciela Boente [aut], Ana Perez-Gonzalez [aut] |
Maintainer: | Ana Perez-Gonzalez <anapg at uvigo.es> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
In views: | MissingData |
CRAN checks: | IPWboxplot results |
Reference manual: | IPWboxplot.pdf |
Vignettes: |
IPWboxplot |
Package source: | IPWboxplot_0.1.2.tar.gz |
Windows binaries: | r-devel: IPWboxplot_0.1.2.zip, r-release: IPWboxplot_0.1.2.zip, r-oldrel: IPWboxplot_0.1.2.zip |
macOS binaries: | r-release (arm64): IPWboxplot_0.1.2.tgz, r-oldrel (arm64): IPWboxplot_0.1.2.tgz, r-release (x86_64): IPWboxplot_0.1.2.tgz, r-oldrel (x86_64): IPWboxplot_0.1.2.tgz |
Old sources: | IPWboxplot archive |
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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.
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