Plot a quantile g-computation object. For qgcomp.glm.noboot, this function will create a butterfly plot of weights. For qgcomp.glm.boot, this function will create a box plot with smoothed line overlaying that represents a non-parametric fit of a model to the expected outcomes in the population at each quantile of the joint exposures (e.g. '1' represents 'at the first quantile for every exposure')
# S3 method for qgcompfit
plot(
x,
suppressprint = FALSE,
pointwisebars = TRUE,
modelfitline = TRUE,
modelband = TRUE,
flexfit = TRUE,
pointwiseref = ceiling(x$q/2),
...
)# S3 method for qgcompmultfit
plot(
x,
suppressprint = FALSE,
pointwisebars = TRUE,
modelfitline = TRUE,
modelband = TRUE,
flexfit = TRUE,
pointwiseref = ceiling(x$q/2),
...
)
"qgcompfit" object from qgcomp.glm.noboot, qgcomp.glm.boot,
qgcomp.cox.noboot, qgcomp.cox.boot, qgcomp.zi.noboot or qgcomp.zi.boot functions
If TRUE, suppresses the plot, rather than printing it by default (it can be saved as a ggplot2 object (or list of ggplot2 objects if x is from a zero- inflated model) and used programmatically) (default = FALSE)
(boot.gcomp only) If TRUE, adds 95% error bars for pointwise comparisons of E(Y|joint exposure) to the smooth regression line plot
(boot.gcomp only) If TRUE, adds fitted (MSM) regression line of E(Y|joint exposure) to the smooth regression line plot
If TRUE, adds 95% prediction bands for E(Y|joint exposure) (the MSM fit)
(boot.gcomp only) if TRUE, adds flexible interpolation of predictions from underlying (conditional) model
(boot.gcomp only) integer: which category of exposure (from 1 to q) should serve as the referent category for pointwise comparisons? (default=1)
unused
plot(qgcompmultfit): Plot method for qgcomp multinomial fits
qgcomp.glm.noboot, qgcomp.glm.boot, and qgcomp