Gcomputation for a set of timefixed exposures with quantilebased basis functions, possibly under linearity and homogeneity assumptions. This approach estimates a regression line corresponding to the expected change in the outcome (on the link basis) given a simultaneous increase in the quantilebased category for all exposures. Works with continuous, binary, and rightcensored timetoevent outcomes. Reference: Alexander P. Keil, Jessie P. Buckley, Katie M. OBrien, Kelly K. Ferguson, Shanshan Zhao, and Alexandra J. White (2019) A quantilebased gcomputation approach to addressing the effects of exposure mixtures; <doi:10.1289/EHP5838>.
Package details 


Author  Alexander Keil [aut, cre] 
Maintainer  Alexander Keil <akeil@unc.edu> 
License  GPL (>= 2) 
Version  2.8.6 
URL  https://github.com/alexpkeil1/qgcomp/ 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.