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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.
Getting started
Browse package contents
Package details |
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| 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@columbia.edu> |
| License | GPL (>= 2) |
| Version | 1.2 |
| URL | https://sites.stat.columbia.edu/gelman/ |
| Package repository | View on CRAN |
| Installation |
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