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Amelia II

Overview

Amelia II is an R package for the multiple imputation of multivariate incomplete data. It uses an algorithm that combines bootstrapping and the EM algorithm to take draws from the posterior of the missing data. The Amelia package includes normalizing transformations, cell-level priors, and methods for handling time-series cross-sectional data.

How to install

To install the latest version of Amelia, which requires R version 2.14.0 or higher, simply use the standard R installation tools:

install.packages("Amelia")

If you would to use the current development release of Amelia (which may be unstable), run the following:

require(devtools)
devtools::install_github("IQSS/Amelia")

Getting started with Amelia

The main function in the Amelia package is amelia() which will perform multiple imputation on a data frame. It allows for easy setting of time-series and unit variables via the ts and cs arguments.

library(Amelia)
data(africa)

a.out <- amelia(africa, m = 5, ts = "year", cs = "country")

AmeliaView GUI

Once installed, you can access most of the Amelia functionality through an interactive GUI by running the following command:

Amelia::AmeliaView()

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Version

Install

install.packages('Amelia')

Monthly Downloads

8,064

Version

1.8.0

License

GPL (>= 2)

Maintainer

Matthew Blackwell

Last Published

May 26th, 2021

Functions in Amelia (1.8.0)

ameliagui

Interactive GUI for Amelia
disperse

Overdispersed starting values diagnostic for multiple imputation
ameliabind

Combine multiple runs of Amelia
AmeliaView

Interactive GUI for Amelia
compare.density

Compare observed versus imputed densities
amelia-package

Amelia II: A Program for Missing Data
combine.output

Combine Multiple Amelia Output Lists
amelia

AMELIA: Multiple Imputation of Incomplete Multivariate Data
freetrade

Trade Policy and Democracy in 9 Asian States
africa

Economic and Political Indictors in 6 African States
transform.amelia

Transform imputed datasets from Amelia objects
overimpute

Overimputation diagnostic plot
moPrep

Prepare Multiple Overimputation Settings
mi.meld

Combine Multiple Results From Multiply Imputed Datasets
missmap

Missingness Map
write.amelia

Write Amelia imputations to file
tscsPlot

Plot observed and imputed time-series for a single cross-section
summary.amelia

Summary of an Amelia object
plot.amelia

Summary plots for Amelia objects