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gim: Generalized Integration Model

Implements the generalized integration model, which integrates individual-level data and summary statistics under a generalized linear model framework. It supports continuous and binary outcomes to be modeled by the linear and logistic regression models. For binary outcome, data can be sampled in prospective cohort studies or case-control studies. Described in Zhang et al. (2020)<doi:10.1093/biomet/asaa014>.

Version: 0.33.1
Depends: R (≥ 3.4.0)
Imports: numDeriv
Suggests: knitr, rmarkdown
Published: 2020-06-12
DOI: 10.32614/CRAN.package.gim
Author: Han Zhang, Kai Yu
Maintainer: Han Zhang <zhangh.ustc at gmail.com>
BugReports: https://github.com/zhangh12/gim/issues
License: MIT + file LICENSE
URL: https://github.com/zhangh12/gim
NeedsCompilation: no
CRAN checks: gim results

Documentation:

Reference manual: gim.pdf
Vignettes: Generalized Integration Model

Downloads:

Package source: gim_0.33.1.tar.gz
Windows binaries: r-devel: gim_0.33.1.zip, r-release: gim_0.33.1.zip, r-oldrel: gim_0.33.1.zip
macOS binaries: r-release (arm64): gim_0.33.1.tgz, r-oldrel (arm64): gim_0.33.1.tgz, r-release (x86_64): gim_0.33.1.tgz, r-oldrel (x86_64): gim_0.33.1.tgz
Old sources: gim archive

Linking:

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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.