SynDI: Synthetic Data Integration

Regression inference for multiple populations by integrating summary-level data using stacked imputations. Gu, T., Taylor, J.M.G. and Mukherjee, B. (2021) A synthetic data integration framework to leverage external summary-level information from heterogeneous populations <doi:10.48550/arXiv.2106.06835>.

Version: 0.1.0
Depends: R (≥ 3.6.0)
Imports: mice, magrittr, dplyr, StackImpute, arm, boot, broom, mvtnorm, randomForest, MASS, knitr
Suggests: markdown
Published: 2022-05-25
Author: Tian Gu [aut], Jeremy M.G. Taylor [aut], Bhramar Mukherjee [aut], Michael Kleinsasser [cre]
Maintainer: Michael Kleinsasser <mkleinsa at umich.edu>
BugReports: https://github.com/umich-biostatistics/SynDI/issues
License: GPL-2
URL: https://github.com/umich-biostatistics/SynDI
NeedsCompilation: no
Materials: README
CRAN checks: SynDI results

Documentation:

Reference manual: SynDI.pdf
Vignettes: SynDI Example 1: Binary Response
SynDI Example 2: Continuous Response

Downloads:

Package source: SynDI_0.1.0.tar.gz
Windows binaries: r-devel: SynDI_0.1.0.zip, r-release: SynDI_0.1.0.zip, r-oldrel: SynDI_0.1.0.zip
macOS binaries: r-release (arm64): SynDI_0.1.0.tgz, r-oldrel (arm64): SynDI_0.1.0.tgz, r-release (x86_64): SynDI_0.1.0.tgz

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