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.


Reference manual

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1.0 by Ben Goodrich, 6 years ago


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, Official Statistics & Survey Statistics

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.

See at CRAN