Amelia II: A Program for Missing Data
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.
See Also
- [Software] AMELIA II: A Program for Missing Data (2009)
- [Software] CLARIFY: Software for Interpreting and Presenting Statistical Results (2003)
- [Software] Zelig: Everyone's Statistical Software (2006)
- [Paper] A Unified Approach to Measurement Error and Missing Data: Details and Extensions (2017)
- [Paper] A Unified Approach to Measurement Error and Missing Data: Overview and Applications (2017)
- [Paper] What to Do About Missing Values in Time Series Cross-Section Data (2010)
- [Presentation] Big Data Is Not About the Data! (2018)
- [Presentation] Big Data Reveals Made Up Data: How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument (2017)