Plot for estimated treatment effect for SensIAT_fulldata_jackknife_results objects

The horizontal and vertical axes represent the sensitivity parameter alpha for the control and treatment groups, respectively. The plot shows at each combination of alpha values zero if the 95% confidence interval contains zero, otherwise the bound of the confidence interval that is closest to zero.

Usage

# S3 method for class 'SensIAT_fulldata_jackknife_results'
autoplot(object, ..., include.rugs = NA)

Arguments

object

A SensIAT_fulldata_jackknife_results object.

...

Additional arguments passed to predict.

include.rugs

If TRUE, adds rugs to the plot. If FALSE, no rugs are added. When NA, rugs are added only if the number of distinct values of alpha_control and alpha_treatment is less than or equal to 10.

Examples

# Note: fitting the jackknife is computationally expensive,
#       so this example is here for reference.
if (FALSE) { # \dontrun{
full.object <-
    fit_SensIAT_fulldata_model(
        data = SensIAT_example_fulldata,
        trt = Treatment_group == 'treatment',
        outcome_modeler = SensIAT_sim_outcome_modeler,
        id = Subject_ID,
        outcome = Outcome,
        time = Time,
        knots = c(60, 260, 460),
        alpha = c(-0.6, -0.3, 0, 0.3, 0.6)
    )
jk.full.model <- jackknife(full.object, time = 180)
ggplot2::autoplot(jk.full.model)
} # }