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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("mi")

1.0 by Ben Goodrich, 4 years ago


http://www.stat.columbia.edu/~gelman/


Browse source code at https://github.com/cran/mi


Authors: 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]


Documentation:   PDF Manual  


Task views: Official Statistics & Survey Methodology, Statistics for the Social Sciences, Missing Data


GPL (>= 2) license


Imports arm

Depends on methods, Matrix, stats4

Suggests betareg, lattice, knitr, MASS, nnet, parallel, sn, survival, truncnorm, foreign


Imported by migui, missCompare, sem.

Suggested by MissingDataGUI.


See at CRAN