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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, r-oldrel (x86_64): SynDI_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=SynDI to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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