Quantile G-Computation

[Up] [Top]

Documentation for package ‘qgcomp’ version 2.16.4

Help Pages

checknames Check for valid model terms in a qgcomp fit
coxmsm_fit Marginal structural Cox model (MSM) fitting within quantile g-computation
gcomp.noboot Quantile g-computation for continuous, binary, and count outcomes under linearity/additivity
glance.qgcompfit Glance at a qgcompfit object
homogeneity_test Hypothesis testing about joint effect of exposures on a multinomial outcome
homogeneity_test.qgcompmultfit Hypothesis testing about 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 joint effect of exposures on a multinomial outcome
joint_test.qgcompmultfit Hypothesis testing about 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
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.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