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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>.

Versions across snapshots

VersionRepositoryFileSize
1.0.2 rolling linux/jammy R-4.5 qgcompint_1.0.2.tar.gz 536.5 KiB
1.0.2 rolling linux/noble R-4.5 qgcompint_1.0.2.tar.gz 536.4 KiB
1.0.2 rolling source/ R- qgcompint_1.0.2.tar.gz 348.5 KiB
1.0.2 latest linux/jammy R-4.5 qgcompint_1.0.2.tar.gz 536.5 KiB
1.0.2 latest linux/noble R-4.5 qgcompint_1.0.2.tar.gz 536.4 KiB
1.0.2 latest source/ R- qgcompint_1.0.2.tar.gz 348.5 KiB
1.0.2 2026-04-26 source/ R- qgcompint_1.0.2.tar.gz 348.5 KiB
1.0.2 2026-04-23 source/ R- qgcompint_1.0.2.tar.gz 348.5 KiB
1.0.2 2026-04-09 windows/windows R-4.5 qgcompint_1.0.2.zip 539.5 KiB
1.0.0 2025-04-20 source/ R- qgcompint_1.0.0.tar.gz 351.0 KiB

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