Package: qgcomp 2.18.4

Alexander Keil

qgcomp: 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, and Alexandra J. White (2019) A quantile-based g-computation approach to addressing the effects of exposure mixtures; <doi:10.1289/EHP5838>.

Authors:Alexander Keil [aut, cre]

qgcomp_2.18.4.tar.gz
qgcomp_2.18.4.zip(r-4.5)qgcomp_2.18.4.zip(r-4.4)qgcomp_2.18.4.zip(r-4.3)
qgcomp_2.18.4.tgz(r-4.5-any)qgcomp_2.18.4.tgz(r-4.4-any)qgcomp_2.18.4.tgz(r-4.3-any)
qgcomp_2.18.4.tar.gz(r-4.5-noble)qgcomp_2.18.4.tar.gz(r-4.4-noble)
qgcomp_2.18.4.tgz(r-4.4-emscripten)qgcomp_2.18.4.tgz(r-4.3-emscripten)
qgcomp.pdf |qgcomp.html✨
qgcomp/json (API)

# Install 'qgcomp' in R:
install.packages('qgcomp', repos = c('https://alexpkeil1.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/alexpkeil1/qgcomp/issues

Datasets:

On CRAN:

Conda:

exposureexposure-mixtureexposure-mixturesquantile-gcomputationsurvival

8.72 score 37 stars 2 packages 70 scripts 1.3k downloads 3 mentions 38 exports 79 dependencies

Last updated 2 days agofrom:62724cdcd9. Checks:1 OK, 8 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 28 2025
R-4.5-winNOTEMar 28 2025
R-4.5-macNOTEMar 28 2025
R-4.5-linuxNOTEMar 28 2025
R-4.4-winNOTEMar 28 2025
R-4.4-macNOTEMar 28 2025
R-4.4-linuxNOTEMar 28 2025
R-4.3-winNOTEMar 28 2025
R-4.3-macNOTEMar 28 2025

Exports:coxmsm_fithomogeneity_testhurdlemsm_fit.controljoint_testmice.impute.leftcenslognormmice.impute.tobitmodelbound.bootmodelbound.eemsm_fitmsm_multinomial_fitmsm.predictpointwisebound.bootpointwisebound.nobootqgcompqgcomp.bootqgcomp.cch.nobootqgcomp.cox.bootqgcomp.cox.nobootqgcomp.eeqgcomp.glm.bootqgcomp.glm.eeqgcomp.glm.nobootqgcomp.hurdle.bootqgcomp.hurdle.nobootqgcomp.multinomial.bootqgcomp.multinomial.nobootqgcomp.nobootqgcomp.partialsqgcomp.survcurve.bootqgcomp.tobit.nobootqgcomp.zi.bootqgcomp.zi.nobootquantizese_combsimdata_quantizedsplit_datavc_combzimsm_fit.control

Dependencies:abindAERarmbackportsbootbroomcarcarDataclicodacodetoolscolorspacecowplotcpp11DerivdigestdoBydplyrfansifarverFormulafuturefuture.applygenericsggplot2globalsgluegridExtragtableisobandlabelinglatticelifecyclelistenvlme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivparallellypbkrtestpillarpkgconfigpsclpurrrquantregR6rbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangrootSolvesandwichscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithrzoo

The qgcomp package: g-computation on exposure quantiles

Alexander Keil

Rendered fromqgcomp-vignette.Rmdusingknitr::knitron Mar 28 2025.

Last update: 2025-03-27
Started: 2018-10-25

Advanced topics for the qgcomp package: time-to-event, clustering, partial effects, weighting, missing data

Alexander Keil

Rendered fromqgcomp-advanced-vignette.Rmdusingknitr::knitron Mar 28 2025.

Last update: 2025-03-27
Started: 2024-06-29

Basic topics for the qgcomp package: g-computation on exposure quantiles

Alexander Keil

Rendered fromqgcomp-basic-vignette.Rmdusingknitr::knitron Mar 28 2025.

Last update: 2025-03-27
Started: 2024-06-29

Readme and manuals

Help Manual

Help pageTopics
Check for valid model terms in a qgcomp fitchecknames
Marginal structural Cox model (MSM) fitting within quantile g-computationcoxmsm_fit
Glance at a qgcompfit objectglance.qgcompfit
Hypothesis testing about a joint effect of exposures on a multinomial outcomehomogeneity_test homogeneity_test.qgcompmultfit
Secondary prediction method for the (hurdle) qgcomp MSM.hurdlemsm_fit
Control of fitting parameters for zero inflated MSMshurdlemsm_fit.control
Hypothesis testing about a joint effect of exposures on a multinomial outcomejoint_test joint_test.qgcompmultfit
Well water datametals
Imputation for limits of detection problemsmice.impute.leftcenslognorm mice.impute.tobit
Estimating qgcomp regression line confidence boundsmodelbound.boot
Estimating qgcomp regression line confidence boundsmodelbound.ee
Fitting marginal structural model (MSM) within quantile g-computationmsm_fit
Fitting marginal structural model (MSM) within quantile g-computationmsm_multinomial_fit
Secondary prediction method for the (non-survival) qgcomp MSM.msm.predict
Default plotting method for a qgcompfit objectplot.qgcompfit plot.qgcompmultfit
Estimating pointwise comparisons for qgcomp.glm.boot objectspointwisebound.boot
Estimating pointwise comparisons for qgcomp.glm.noboot objectspointwisebound.noboot
Default prediction method for a qgcompfit object (non-survival outcomes only)predict.qgcompfit
Default printing method for a qgcompfit objectprint.qgcompfit
Quantile g-computation for continuous, binary, count, and censored survival outcomesqgcomp
Quantile g-computation for survival outcomes in a case-cohort design under linearity/additivityqgcomp.cch.noboot
Quantile g-computation for survival outcomesqgcomp.cox.boot
Quantile g-computation for survival outcomes under linearity/additivityqgcomp.cox.noboot
Quantile g-computation for continuous and binary outcomesqgcomp.boot qgcomp.glm.boot
Quantile g-computation for continuous and binary outcomesqgcomp.ee qgcomp.glm.ee
Quantile g-computation for continuous, binary, and count outcomes under linearity/additivityqgcomp.glm.noboot qgcomp.noboot
Quantile g-computation for hurdle count outcomesqgcomp.hurdle.boot
Quantile g-computation for hurdle count outcomes under linearity/additivityqgcomp.hurdle.noboot
Quantile g-computation for multinomial outcomesqgcomp.multinomial.boot
Quantile g-computation for multinomial outcomesqgcomp.multinomial.noboot
Partial effect sizes, confidence intervals, hypothesis testsqgcomp.partials
Survival curve data from a qgcomp survival fitqgcomp.survcurve.boot
Quantile g-computation for left-censored outcomesqgcomp.tobit.noboot
Quantile g-computation for zero-inflated count outcomesqgcomp.zi.boot
Quantile g-computation for zero-inflated count outcomes under linearity/additivityqgcomp.zi.noboot
Quantizing exposure dataquantize
Calculate standard error of weighted linear combination of random variablesse_comb
Simulate quantized exposures for testing methodssimdata_quantized
Perform sample splittingsplit_data
Summarize gcompmultfit objectsummary.qgcompmultfit
Tidy method for qgcompfit objecttidy.qgcompfit
Calculate covariance matrix between one random variable and a linear combination of random variablesvc_comb
Secondary prediction method for the (zero-inflated) qgcomp MSM.zimsm_fit
Control of fitting parameters for zero inflated MSMszimsm_fit.control