# Quantile G-Computation

## Documentation for package ‘qgcomp’ version 2.18.4

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

checknames | Check for valid model terms in a qgcomp fit
coxmsm_fit | Marginal structural Cox model (MSM) fitting within quantile g-computation
glance.qgcompfit | Glance at a qgcompfit object
homogeneity_test | Hypothesis testing about a joint effect of exposures on a multinomial outcome
homogeneity_test.qgcompmultfit | Hypothesis testing about a joint effect of exposures on a multinomial outcome
hurdlemsm_fit | Secondary prediction method for the (hurdle) qgcomp MSM.
hurdlemsm_fit.control | Control of fitting parameters for zero inflated MSMs
joint_test | Hypothesis testing about a joint effect of exposures on a multinomial outcome
joint_test.qgcompmultfit | Hypothesis testing about a joint effect of exposures on a multinomial outcome
metals | Well water data
mice.impute.leftcenslognorm | Imputation for limits of detection problems
mice.impute.tobit | Imputation for limits of detection problems
modelbound.boot | Estimating qgcomp regression line confidence bounds
modelbound.ee | Estimating qgcomp regression line confidence bounds
msm.predict | Secondary prediction method for the (non-survival) qgcomp MSM.
msm_fit | Fitting marginal structural model (MSM) within quantile g-computation
msm_multinomial_fit | Fitting marginal structural model (MSM) within quantile g-computation
plot.qgcompfit | Default plotting method for a qgcompfit object
plot.qgcompmultfit | Default plotting method for a qgcompfit object
pointwisebound.boot | Estimating pointwise comparisons for qgcomp.glm.boot objects
pointwisebound.noboot | Estimating pointwise comparisons for qgcomp.glm.noboot objects
predict.qgcompfit | Default prediction method for a qgcompfit object (non-survival outcomes only)
print.qgcompfit | Default printing method for a qgcompfit object
qgcomp | Quantile g-computation for continuous, binary, count, and censored survival outcomes
qgcomp.boot | Quantile g-computation for continuous and binary outcomes
qgcomp.cch.noboot | Quantile g-computation for survival outcomes in a case-cohort design under linearity/additivity
qgcomp.cox.boot | Quantile g-computation for survival outcomes
qgcomp.cox.noboot | Quantile g-computation for survival outcomes under linearity/additivity
qgcomp.ee | Quantile g-computation for continuous and binary outcomes
qgcomp.glm.boot | Quantile g-computation for continuous and binary outcomes
qgcomp.glm.ee | Quantile g-computation for continuous and binary outcomes
qgcomp.glm.noboot | Quantile g-computation for continuous, binary, and count outcomes under linearity/additivity
qgcomp.hurdle.boot | Quantile g-computation for hurdle count outcomes
qgcomp.hurdle.noboot | Quantile g-computation for hurdle count outcomes under linearity/additivity
qgcomp.multinomial.boot | Quantile g-computation for multinomial outcomes
qgcomp.multinomial.noboot | Quantile g-computation for multinomial outcomes
qgcomp.noboot | Quantile g-computation for continuous, binary, and count outcomes under linearity/additivity
qgcomp.partials | Partial effect sizes, confidence intervals, hypothesis tests
qgcomp.survcurve.boot | Survival curve data from a qgcomp survival fit
qgcomp.tobit.noboot | Quantile g-computation for left-censored outcomes
qgcomp.zi.boot | Quantile g-computation for zero-inflated count outcomes
qgcomp.zi.noboot | Quantile g-computation for zero-inflated count outcomes under linearity/additivity
quantize | Quantizing exposure data
se_comb | Calculate standard error of weighted linear combination of random variables
simdata_quantized | Simulate quantized exposures for testing methods
split_data | Perform sample splitting
summary.qgcompmultfit | Summarize gcompmultfit object
tidy.qgcompfit | Tidy method for qgcompfit object
vc_comb | Calculate covariance matrix between one random variable and a linear combination of random variables
zimsm_fit | Secondary prediction method for the (zero-inflated) qgcomp MSM.
zimsm_fit.control | Control of fitting parameters for zero inflated MSMs