sdglinkage: Synthetic Data Generation for Linkage Methods Development

A tool for synthetic data generation that can be used for linkage method development, with elements of i) gold standard file with complete and accurate information and ii) linkage files that are corrupted as we often see in raw dataset.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: bnlearn (≥ 4.4.1), synthpop (≥ 1.5.1), reshape (≥ 0.8.8), ggplot2 (≥ 3.1.1), visNetwork (≥ 2.0.6), arsenal (≥ 3.3.0)
Suggests: mlr (≥ 2.16.0), PostcodesioR (≥ 0.1.1), reclin, dplyr, knitr, rmarkdown, testthat
Published: 2020-04-27
Author: Haoyuan Zhang, Katie Harron, Harvey Goldstein, Andrew Boyd, Ruth Gilbert
Maintainer: Haoyuan Zhang <howardhyzhang at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: sdglinkage results

Downloads:

Reference manual: sdglinkage.pdf
Vignettes: From Sensitive Real Identifiers to Synthetic Identifiers
Generation of Gold Standard File and Linkage Files
Synthetic Data Generation and Evaluation
sdglinkage_README
Package source: sdglinkage_0.1.0.tar.gz
Windows binaries: r-devel: sdglinkage_0.1.0.zip, r-release: sdglinkage_0.1.0.zip, r-oldrel: sdglinkage_0.1.0.zip
macOS binaries: r-release (arm64): sdglinkage_0.1.0.tgz, r-release (x86_64): sdglinkage_0.1.0.tgz, r-oldrel: sdglinkage_0.1.0.tgz

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