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qgcompint  

Quantile G-Computation Extensions for Effect Measure Modification
View on CRAN: Click here


Download and install qgcompint package within the R console
Install from CRAN:
install.packages("qgcompint")

Install from Github:
library("remotes")
install_github("cran/qgcompint")

Install by package version:
library("remotes")
install_version("qgcompint", "1.0.0")



Attach the package and use:
library("qgcompint")
Maintained by
Alexander Keil
[Scholar Profile | Author Map]
First Published: 2021-09-20
Latest Update: 2022-03-22
Description:
G-computation for a set of time-fixed exposures with quantile-based basis functions, possibly under linearity and homogeneity assumptions. Effect measure modification in this method is a way to assess how the effect of the mixture varies by a binary, categorical or continuous variable. Reference: Alexander P. Keil, Jessie P. Buckley, Katie M. OBrien, Kelly K. Ferguson, Shanshan Zhao, and Alexandra J. White (2019) A quantile-based g-computation approach to addressing the effects of exposure mixtures; .
How to cite:
Alexander Keil (2021). qgcompint: Quantile G-Computation Extensions for Effect Measure Modification. R package version 1.0.0, https://cran.r-project.org/web/packages/qgcompint. Accessed 01 May. 2025.
Previous versions and publish date:
0.6.2 (2021-09-20 10:20), 0.6.6 (2021-12-11 20:30), 0.7.0 (2022-03-22 17:00)
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Complete documentation for qgcompint
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