Quantile G-Computation Extensions for Effect Measure Modification


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Documentation for package ‘qgcompint’ version 1.0.0

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getjointeffects Calculate joint effect of mixture effect and modifier vs. common referent
getstrateffects Calculate mixture effect at a set value of effect measure modifier
getstratweights Calculate weights at a set value of effect measure modifier
modelbound Estimating qgcomp regression line confidence bounds
plot.qgcompemmfit Default plotting method for a qgcompemmfit object
pointwisebound Estimating pointwise comparisons for qgcompemmfit objects
print.qgcompemmfit Default printing method for a qgcompemmfit object
qgcomp.emm.boot EMM for Quantile g-computation for continuous, binary, and count outcomes under non-linearity/non-additivity or clustered data
qgcomp.emm.cox.noboot EMM for Quantile g-computation with survival outcomes under linearity/additivity
qgcomp.emm.ee EMM for Quantile g-computation for continuous, binary, and count outcomes under linearity/additivity
qgcomp.emm.glm.boot EMM for Quantile g-computation for continuous, binary, and count outcomes under non-linearity/non-additivity or clustered data
qgcomp.emm.glm.ee EMM for Quantile g-computation for continuous, binary, and count outcomes under linearity/additivity
qgcomp.emm.glm.noboot EMM for Quantile g-computation for continuous, binary, and count outcomes under linearity/additivity
qgcomp.emm.noboot EMM for Quantile g-computation for continuous, binary, and count outcomes under linearity/additivity
simdata_quantized_emm Simulate quantized exposures for testing methods