mi: Missing Data Imputation and Model Checking

The mi package provides functions for data manipulation, imputing missing values in an approximate Bayesian framework, diagnostics of the models used to generate the imputations, confidence-building mechanisms to validate some of the assumptions of the imputation algorithm, and functions to analyze multiply imputed data sets with the appropriate degree of sampling uncertainty.

Version: 1.0
Depends: R (≥ 3.0.0), methods, Matrix, stats4
Imports: arm (≥ 1.4-11)
Suggests: betareg, lattice, knitr, MASS, nnet, parallel, sn, survival, truncnorm, foreign
Published: 2015-04-16
Author: Andrew Gelman [ctb], Jennifer Hill [ctb], Yu-Sung Su [aut], Masanao Yajima [ctb], Maria Pittau [ctb], Ben Goodrich [cre, aut], Yajuan Si [ctb], Jon Kropko [aut]
Maintainer: Ben Goodrich <benjamin.goodrich at columbia.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.stat.columbia.edu/~gelman/
NeedsCompilation: no
Citation: mi citation info
In views: OfficialStatistics, SocialSciences
CRAN checks: mi results


Reference manual: mi.pdf
Vignettes: An Example of mi Usage
Package source: mi_1.0.tar.gz
Windows binaries: r-devel: mi_1.0.zip, r-release: mi_1.0.zip, r-oldrel: mi_1.0.zip
OS X El Capitan binaries: r-release: mi_1.0.tgz
OS X Mavericks binaries: r-oldrel: mi_1.0.tgz
Old sources: mi archive

Reverse dependencies:

Reverse imports: migui, sem
Reverse suggests: MissingDataGUI


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