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mi (version 1.3.1)

Missing Data Imputation and Model Checking

Description

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.

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Version

Install

install.packages('mi')

Monthly Downloads

19,583

Version

1.3.1

License

GPL (>= 2)

Maintainer

Ben Goodrich

Last Published

July 28th, 2026

Functions in mi (1.3.1)

censored-continuous-class

The "censored-continuous" Class, the "truncated-continuous" Class and Inherited Classes
count-class

Class "count"
rdata.frame

Generate a random data.frame with tunable characteristics
mipply

Apply a Function to a Object of Class mi
experiment_missing_data.frame

Class "experiment_missing_data.frame"
semi-continuous-class

Class "semi-continuous" and Inherited Classes
continuous

Class "continuous"
hist

Histograms of Multiply Imputed Data
positive-continuous-class

Class "positive-continuous" and Inherited Classes
multinomial

The multinomial family
irrelevant

Class "irrelevant" and Inherited Classes
multilevel_missing_data.frame

Class "multilevel_missing_data.frame"
fit_model

Wrappers To Fit a Model
categorical

Class "categorical" and Inherited Classes
nlsyV

National Longitudinal Survey of Youth Extract
mi-internal

Internal Functions and Methods
mi2stata

Exports completed data in Stata (.dta) or comma-separated (.csv) format
06pool

Estimate a Model Pooling Over the Imputed Datasets
CHAIN

Subset of variables from the CHAIN project
07complete

Extract the Completed Data
05Rhats

Convergence Diagnostics
01missing_variable

Class "missing_variable" and Inherited Classes
00mi-package

Iterative Multiple Imputation from Conditional Distributions
04mi

Multiple Imputation
02missing_data.frame

Class "missing_data.frame"
get_parameters

An Extractor Function for Model Parameters
allcategorical_missing_data.frame

Class "allcategorical_missing_data.frame"
03change

Make Changes to Discretionary Characteristics of Missing Variables
bounded-continuous-class

Class "bounded-continuous"