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. 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; <arXiv:1902.04200> [stat.ME].
|Author||Alexander Keil [aut, cre]|
|Maintainer||Alexander Keil <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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