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>.
Version: 2.18.4 Depends: R (≥ 3.5.0) Imports: AER, arm, future, future.apply, generics, ggplot2 (≥ 3.3.0), grDevices, grid, gridExtra, nnet, numDeriv, pscl, rootSolve, stats, survival, tibble Suggests: broom, devtools, knitr, markdown, MASS, mice Published: 2025-03-28 DOI: 10.32614/CRAN.package.qgcomp Author: Alexander Keil [aut, cre] Maintainer: Alexander Keil <alex.keil at nih.gov> BugReports: https://github.com/alexpkeil1/qgcomp/issues License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://github.com/alexpkeil1/qgcomp/ NeedsCompilation: no Language: en-US Materials: README, NEWS CRAN checks: qgcomp results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=qgcomp to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4