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 |
DOI: | 10.32614/CRAN.package.SynDI |
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 |
Reference manual: | SynDI.pdf |
Vignettes: |
SynDI Example 1: Binary Response SynDI Example 2: Continuous Response |
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 |
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