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qgcompint: Quantile G-Computation Extensions for Effect Measure Modification
G-computation for a set of time-fixed exposures with quantile-based basis functions, possibly under linearity and homogeneity assumptions. Effect measure modification in this method is a way to assess how the effect of the mixture varies by a binary, categorical or continuous variable. 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>.
Browse package contents
Package details |
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| Author | Alexander Keil [aut, cre] |
| Maintainer | Alexander Keil <alex.keil@nih.gov> |
| License | GPL (>= 2) |
| Version | 1.0.0 |
| URL | https://github.com/alexpkeil1/qgcompint/ |
| Package repository | View on CRAN |
| Installation |
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