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.

Package details

AuthorAndrew 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]
MaintainerBen Goodrich <benjamin.goodrich@columbia.edu>
LicenseGPL (>= 2)
URL http://www.stat.columbia.edu/~gelman/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the mi package in your browser

Any scripts or data that you put into this service are public.

mi documentation built on June 7, 2022, 1:04 a.m.