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.

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]
Date of publication2015-04-16 19:53:48
MaintainerBen Goodrich <benjamin.goodrich@columbia.edu>
LicenseGPL (>= 2)
Version1.0
http://www.stat.columbia.edu/~gelman/

View on CRAN

Man pages

00mi-package: Iterative Multiple Imputation from Conditional Distributions

01missing_variable: Class "missing_variable" and Inherited Classes

02missing_data.frame: Class "missing_data.frame"

03change: Make Changes to Discretionary Characteristics of Missing...

04mi: Multiple Imputation

05Rhats: Convergence Diagnostics

06pool: Estimate a Model Pooling Over the Imputed Datasets

07complete: Extract the Completed Data

allcategorical_missing_data.frame: Class "allcategorical_missing_data.frame"

bounded: Class "bounded-continuous"

categorical: Class "categorical" and Inherited Classes

censored-continuous: The "censored-continuous" Class, the "truncated-continuous"...

CHAIN: Subset of variables from the CHAIN project

continuous: Class "continuous"

count: Class "count"

experiment_missing_data.frame: Class "experiment_missing_data.frame"

fit_model: Wrappers To Fit a Model

get_parameters: An Extractor Function for Model Parameters

hist: Histograms of Multiply Imputed Data

irrelevant: Class "irrelevant" and Inherited Classes

mi2stata: Exports completed data in Stata (.dta) or comma-separated...

mi-internal: Internal Functions and Methods

mipply: Apply a Function to a Object of Class mi

multilevel_missing_data.frame: Class "multilevel_missing_data.frame"

multinomial: The multinomial family

nlsyV: National Longitudinal Survey of Youth Extract

positive: Class "positive-continuous" and Inherited Classes

rdata.frame: Generate a random data.frame with tunable characteristics

semi-continuous: Class "semi-continuous" and Inherited Classes

Files in this package

mi
mi/inst
mi/inst/CITATION
mi/inst/doc
mi/inst/doc/mi_vignette.pdf
mi/inst/doc/mi_vignette.Rmd
mi/inst/doc/mi_vignette.R
mi/tests
mi/tests/missing_variable.R
mi/tests/missing_data.frame.R
mi/NAMESPACE
mi/data
mi/data/nlsyV.RData
mi/data/CHAIN.RData
mi/R
mi/R/change_link.R mi/R/change_imputation_method.R mi/R/debug.R mi/R/mi.R mi/R/AllClass.R
mi/R/sysdata.rda
mi/R/convenience.R mi/R/plot_methods.R mi/R/get_parameters.R mi/R/missing_variable.R mi/R/random_df.R mi/R/change_size.R mi/R/change.R mi/R/change_type.R mi/R/change_model.R mi/R/tobin5.R mi/R/fit_model.R mi/R/pool.R mi/R/change_family.R mi/R/AllGeneric.R mi/R/change_transformation.R mi/R/missing_data.frame.R mi/R/misc.R mi/R/complete.R mi/R/hist_methods.R mi/R/zzz.R
mi/vignettes
mi/vignettes/mi_vignette.Rmd
mi/MD5
mi/build
mi/build/vignette.rds
mi/build/partial.rdb
mi/DESCRIPTION
mi/man
mi/man/censored-continuous.Rd mi/man/mi2stata.Rd mi/man/00mi-package.Rd mi/man/03change.Rd mi/man/04mi.Rd mi/man/06pool.Rd mi/man/continuous.Rd mi/man/nlsyV.Rd mi/man/07complete.Rd mi/man/mi-internal.Rd mi/man/CHAIN.Rd mi/man/categorical.Rd mi/man/rdata.frame.Rd mi/man/positive.Rd mi/man/semi-continuous.Rd mi/man/irrelevant.Rd mi/man/fit_model.Rd mi/man/05Rhats.Rd mi/man/hist.Rd mi/man/mipply.Rd mi/man/01missing_variable.Rd mi/man/bounded.Rd mi/man/multilevel_missing_data.frame.Rd mi/man/allcategorical_missing_data.frame.Rd mi/man/count.Rd mi/man/02missing_data.frame.Rd mi/man/get_parameters.Rd mi/man/multinomial.Rd mi/man/experiment_missing_data.frame.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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