A Program for Missing Data

A tool that "multiply imputes" missing data in a single cross-section (such as a survey), from a time series (like variables collected for each year in a country), or from a time-series-cross-sectional data set (such as collected by years for each of several countries). Amelia II implements our bootstrapping-based algorithm that gives essentially the same answers as the standard IP or EMis approaches, is usually considerably faster than existing approaches and can handle many more variables. Unlike Amelia I and other statistically rigorous imputation software, it virtually never crashes (but please let us know if you find to the contrary!). The program also generalizes existing approaches by allowing for trends in time series across observations within a cross-sectional unit, as well as priors that allow experts to incorporate beliefs they have about the values of missing cells in their data. Amelia II also includes useful diagnostics of the fit of multiple imputation models. The program works from the R command line or via a graphical user interface that does not require users to know R.

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()