qgcomp (1.2.0)

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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 Alexandra J. White (2019) A quantile-based g-computation approach to addressing the effects of exposure mixtures; [stat.ME].

Maintainer: Alexander Keil
Author(s): Alexander Keil [aut, cre]

License: GPL (>= 2)

Uses: arm, future, future.apply, ggplot2, gridExtra, survival, knitr

Released 26 days ago.

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