Package: gim 0.34.2

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>.

Authors:Han Zhang, Kai Yu

gim_0.34.2.tar.gz
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gim.pdf |gim.html
gim/json (API)

# Install 'gim' in R:
install.packages('gim', repos = c('https://zhangh12.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/zhangh12/gim/issues

Datasets:
  • dat - Data for example in 'gim'

On CRAN:

Conda:

3.00 score 5 scripts 182 downloads 1 exports 1 dependencies

Last updated 4 years agofrom:f8ebca8e67. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 12 2025
R-4.5-winOKMar 12 2025
R-4.5-macOKMar 12 2025
R-4.5-linuxOKMar 12 2025
R-4.4-winOKMar 12 2025
R-4.4-macOKMar 12 2025
R-4.4-linuxOKMar 12 2025
R-4.3-winOKMar 12 2025
R-4.3-macOKMar 12 2025

Exports:gim

Dependencies:numDeriv

Generalized Integration Model

Rendered fromgim.Rmdusingknitr::rmarkdownon Mar 12 2025.

Last update: 2020-06-24
Started: 2020-02-18