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mitml

Tools for multiple imputation in multilevel modeling

This R package provides tools for multiple imputation of missing data in multilevel modeling. It includes a user-friendly interface to the packages pan and jomo, and several functions for visualization, data management, and the analysis of multiply imputed data sets.

The purpose of mitml is to provide users with a set of effective and user-friendly tools for multiple imputation of multilevel data without requiring advanced knowledge of its statistical underpinnings. Examples and additional information can be found in the official documentation of the package and in the Wiki pages on GitHub.

If you use mitml and have suggestions for improvement, please email me (see here) or file an issue at the GitHub repository.

CRAN version

The official version of mitml is hosted on CRAN and may be found here. The CRAN version can be installed from within R using:

install.packages("mitml")

GitHub version

The version hosted here is the development version of mitml, allowing better tracking of issues and possibly containing features and changes in advance. The GitHub version can be installed using devtools as:

install.packages("devtools")
devtools::install_github("simongrund1/mitml")

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Version

Install

install.packages('mitml')

Monthly Downloads

45,597

Version

0.4-5

License

GPL (>= 2)

Maintainer

Last Published

March 8th, 2023

Functions in mitml (0.4-5)

read.mitml

Read mitml objects from file
mids2mitml.list

Convert objects of class mids to mitml.list
plot.mitml

Print diagnostic plots
panImpute

Impute multilevel missing data using pan
mitmlComplete

Extract imputed data sets
mitml.list2mids

Convert objects of class mitml.list to mids
confint.mitml.testEstimates

Summarize and extract pooled parameter estimates
sort.mitml.list

Sort a list of imputed data sets
mitml-package

mitml: Tools for multiple imputation in multilevel modeling
multilevelR2

Calculate R-squared measures for multilevel models
studentratings

Example data set on student ratings and achievement
testEstimates

Compute final estimates and inferences
testConstraints

Test functions and constraints of model parameters
write.mitmlSAV

Write mitml objects to native SPSS format
write.mitml

Write mitml objects to file
write.mitmlMplus

Write mitml objects to Mplus format
testModels

Test multiple parameters and compare nested models
summary.mitml

Summary measures for imputation models
subset.mitml.list

Subset a list of imputed data sets
with.mitml.list

Evaluate an expression in a list of imputed data sets
write.mitmlSPSS

Write mitml objects to SPSS compatible format
amelia2mitml.list

Convert objects of class amelia to mitml.list
long2mitml.list

Convert imputations from long format to mitml.list
as.mitml.list

Convert a list of data sets to mitml.list
clusterMeans

Calculate cluster means
c.mitml.list

Concatenate lists of imputed data sets
is.mitml.list

Check if an object is of class mitml.list
justice

Example data set on employees' justice perceptions and satisfaction
anova.mitml.result

Compare several nested models
leadership

Example data set on leadership style and job satisfaction
jomoImpute

Impute single-level and multilevel missing data using jomo