qgcomp: Quantile G-Computation

G-computation for a set of time-fixed exposures with quantile-based 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 quantile-based category for all exposures. Works with continuous, binary, and right-censored time-to-event outcomes. 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; <doi:10.1289/EHP5838>.

Package details

AuthorAlexander Keil [aut, cre]
MaintainerAlexander Keil <akeil@unc.edu>
LicenseGPL (>= 2)
URL https://github.com/alexpkeil1/qgcomp/
Package repositoryView on CRAN
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qgcomp documentation built on Jan. 24, 2022, 5:08 p.m.