<b>Amelia</b>II: A Program for Missing Data

TLDR

Amelia II is a complete R package for multiple imputation of missing data. The package uses a fast expectation‑maximization with bootstrapping algorithm that supports Bayesian priors on individual cells, handles cross‑sectional and time‑series data, and provides graphical diagnostics, outperforming MCMC approaches in speed and scalability while yielding comparable results. The program is easy to use, robust, and offers both a simple command line and an extensive graphical user interface.

Abstract

Amelia II is a complete R package for multiple imputation of missing data. The package implements a new expectation-maximization with bootstrapping algorithm that works faster, with larger numbers of variables, and is far easier to use, than various Markov chain Monte Carlo approaches, but gives essentially the same answers. The program also improves imputation models by allowing researchers to put Bayesian priors on individual cell values, thereby including a great deal of potentially valuable and extensive information. It also includes features to accurately impute cross-sectional datasets, individual time series, or sets of time series for different cross-sections. A full set of graphical diagnostics are also available. The program is easy to use, and the simplicity of the algorithm makes it far more robust; both a simple command line and extensive graphical user interface are included.