Package: Amelia 1.8.3

Amelia: 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.

Authors:James Honaker [aut], Gary King [aut], Matthew Blackwell [aut, cre]

Amelia_1.8.3.tar.gz
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Amelia_1.8.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
Amelia/json (API)

# Install 'Amelia' in R:
install.packages('Amelia', repos = c('https://mattblackwell.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • africa - Economic and Political Indictors in 6 African States
  • freetrade - Trade Policy and Democracy in 9 Asian States

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

9.26 score 1 stars 13 packages 2.2k scripts 10k downloads 106 mentions 16 exports 4 dependencies

Last updated from:2db0588446. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK152
linux-devel-x86_64OK155
source / vignettesOK187
linux-release-arm64OK152
linux-release-x86_64OK150
macos-release-arm64OK83
macos-release-x86_64OK228
macos-oldrel-arm64OK84
macos-oldrel-x86_64OK177
windows-develOK133
windows-releaseOK128
windows-oldrelOK129
wasm-releaseOK155

Exports:ameliaamelia.defaultamelia.molistameliabindAmeliaViewcompare.densitydispersemi.combinemi.meldmissmapmoPrepoverimputetransform.ameliatscsPlotwith.ameliawrite.amelia

Dependencies:foreignRcppRcppArmadillorlang

Introduction to Multiple Imputation
Introduction | What Amelia Does | Assumptions | Algorithm | Analysis | References

Last update: 2024-11-08
Started: 2021-05-26

Using Amelia
Data | Multiple Imputation | Saving imputed datasets | Combining multiple calls to amelia() | Screen output | Parallel Imputation | Improving Imputations via Transformations | Ordinal | Nominal | Natural log | Square root | Logistic | Identification Variables | Time Series, or Time Series Cross Sectional Data | Lags and leads | Including Prior Information | Ridge priors for high missingness, Small samples, or large correlations | Observation-level priors | Logical bounds | Post-imputations Transformations | Analysis Models | The amelia class | References

Last update: 2024-11-08
Started: 2021-05-26

AmeliaView GUI Guide
Loading AmeliaView | Loading data into AmeliaView | Variable Dashboard | Amelia Options | Numerical options | Add Distributional Prior | Add Range Prior | Imputing and checking diagnostics | Diagnostics Dialog | Sessions

Last update: 2021-05-26
Started: 2021-05-26

Multiple Imputation Diagnostics
Overimpute | Overdispersed Starting Values | Time-series Plots | Missingness maps | References

Last update: 2021-05-26
Started: 2021-05-26