Package: mi 1.1

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.

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]

mi_1.1.tar.gz
mi_1.1.zip(r-4.5)mi_1.1.zip(r-4.4)mi_1.1.zip(r-4.3)
mi_1.1.tgz(r-4.4-any)mi_1.1.tgz(r-4.3-any)
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mi_1.1.tgz(r-4.4-emscripten)mi_1.1.tgz(r-4.3-emscripten)
mi.pdf |mi.html✨
mi/json (API)

# Install 'mi' in R:
install.packages('mi', repos = c('https://bgoodri.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • CHAIN - Subset of variables from the CHAIN project
  • nlsyV - National Longitudinal Survey of Youth Extract

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

8.21 score 2 stars 45 packages 228 scripts 26k downloads 30 mentions 27 exports 13 dependencies

Last updated 2 years agofrom:d2eadcfdcb. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-winWARNINGNov 15 2024
R-4.5-linuxWARNINGNov 15 2024
R-4.4-winWARNINGNov 15 2024
R-4.4-macWARNINGNov 15 2024
R-4.3-winWARNINGNov 15 2024
R-4.3-macWARNINGNov 15 2024

Exports:.possible_missing_variable.prunechangechange_familychange_imputation_methodchange_linkchange_modelchange_sizechange_transformationchange_typecompletedisplayfit_modelget_parametershistimagemimi2BUGSmi2statamipplymissing_data.framemissing_variablemultinomialplotpoolrdata.frameRhats

Dependencies:abindarmbootcodalatticelme4MASSMatrixminqanlmenloptrRcppRcppEigen

An Example of mi Usage

Ben Goodrich and Jonathan Kropko, for this version, based on earlier versions written by Yu-Sung Su, Masanao Yajima, Maria Grazia Pittau, Jennifer Hill, and Andrew Gelman

Rendered frommi_vignette.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2015-04-16
Started: 2015-04-16

Readme and manuals

Help Manual

Help pageTopics
Iterative Multiple Imputation from Conditional Distributionsmi-package
Class "missing_variable" and Inherited Classes01missing_variable MatrixTypeThing-class missing_variable missing_variable-class WeAreFamily-class
Class "missing_data.frame"02missing_data.frame missing_data.frame missing_data.frame-class
Make Changes to Discretionary Characteristics of Missing Variables03change change change-methods change_family change_imputation_method change_link change_model change_size change_transformation change_type
Multiple Imputation04mi mi mi-class mi-methods
Convergence Diagnostics05Rhats mi2BUGS Rhats
Estimate a Model Pooling Over the Imputed Datasets06pool display,pooled-method pool pooled-class pooled-methods
Extract the Completed Data07complete complete complete-methods
Class "allcategorical_missing_data.frame"allcategorical_missing_data.frame allcategorical_missing_data.frame-class
Class "bounded-continuous"bounded-continuous bounded-continuous-class
Class "categorical" and Inherited Classesbinary-class categorical categorical-class grouped-binary-class interval-class ordered-categorical-class unordered-categorical-class
The "censored-continuous" Class, the "truncated-continuous" Class and Inherited Classescensored-continuous censored-continuous-class FF_censored-continuous-class FF_truncated-continuous-class FN_censored-continuous-class FN_truncated-continuous-class NF_censored-continuous-class NF_truncated-continuous-class NN_censored-continuous-class NN_truncated-continuous-class truncated-continuous truncated-continuous-class
Subset of variables from the CHAIN projectCHAIN
Class "continuous"continuous continuous-class
Class "count"count-class
Class "experiment_missing_data.frame"experiment_missing_data.frame experiment_missing_data.frame-class
Wrappers To Fit a Modelfit_model fit_model-methods
An Extractor Function for Model Parametersget_parameters get_parameters-methods
Histograms of Multiply Imputed Datahist hist-methods
Class "irrelevant" and Inherited Classesfixed-class group-class irrelevant irrelevant-class
Exports completed data in Stata (.dta) or comma-separated (.csv) formatmi2stata
Apply a Function to a Object of Class mimipply
Class "multilevel_missing_data.frame"multilevel_missing_data.frame multilevel_missing_data.frame-class
The multinomial familymultinomial
National Longitudinal Survey of Youth ExtractnlsyV
Class "positive-continuous" and Inherited Classespositive-continuous-class proportion-class
Generate a random data.frame with tunable characteristicsrdata.frame
Class "semi-continuous" and Inherited Classesnonnegative-continuous nonnegative-continuous-class SC_proportion SC_proportion-class semi-continuous semi-continuous-class