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.
Version: |
1.7.6 |
Depends: |
R (≥ 3.0.2), Rcpp (≥ 0.11) |
Imports: |
foreign, utils, grDevices, graphics, methods, stats |
LinkingTo: |
Rcpp (≥ 0.11), RcppArmadillo |
Suggests: |
tcltk, Zelig |
Published: |
2019-11-25 |
Author: |
James Honaker,
Gary King,
Matthew Blackwell |
Maintainer: |
Matthew Blackwell <mblackwell at gov.harvard.edu> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: |
http://gking.harvard.edu/amelia |
NeedsCompilation: |
yes |
Citation: |
Amelia citation info |
Materials: |
README NEWS |
In views: |
MissingData, OfficialStatistics, SocialSciences |
CRAN checks: |
Amelia results |