compute_cumcount_ci.Rdcompute_cumcount_ci is a function that computes confidence intervals for cumulative
count estimates using the influence curve or supplied bootstrap replicates to
estimate standard errors.
compute_cumcount_ci(
obj,
alpha = 0.05,
ic = FALSE,
count_time = NULL,
boot_method = "log-normal"
)A cumcount object containing the count estimates, e.g., as computed by estimate_ipwcount
The desired nominal significance level of the confidence intervals.
If the supplied object contains a bootstrap count estimates, setting ic = TRUE will requests that estimated standard errors be derived from the influence curve.
The time at which the cumulative count estimates should be returned (the default value NULL returns all times)
The specific bootstrap approach used to compute confidence
intervals. Options are "log-normal" (default; normal approximation on the
log scale), "normal" (normal approximation on the count scale),
"percentile" (percentile-based approach using quantiles of the bootstrap
distribution), and "basic" (basic bootstrap using the reflection method).
When obj was created without using bootstrap estimation or ic = TRUE is
provided then the value of boot_method is ignored.
A matrix containing the cumulative count and confidence interval for each time point and treatment group.