confint.margstd_boot {risks}

Bootstrap confidence intervals

Description

Confidence intervals for models fit using marginal standardization based on parametric bootstrapping.

Usage

## S3 method for class 'margstd_boot'
confint(
  object,
  parm = NULL,
  level = 0.95,
  bootrepeats = 1000,
  bootci = c("bca", "normal", "nonpar"),
  jacksd = FALSE,
  ...
)

Arguments

object

Model fitted through marginal standardization

parm

Not used, for compatibility

level

Confidence level, defaults to 0.95.

bootrepeats

Bootstrap repeats. Defaults to 1000. Consider increasing.

bootci

Type of bootstrap confidence interval:

• "bca" Default. Parametric BCa (bias-corrected accelerated) confidence intervals.

• "normal" Parametric normality-based confidence intervals, which require lower repeat numbers but are less accurate and may result in invalid results for ratios.

• "nonpar" Non-parametric BCa confidence intervals, which should be used with caution because of the risk of sparse-data bias with non-parametric bootstrapping.

jacksd

Return jackknife Monte-Carlo error for the confidence limits? Only functional with BCa confidence intervals. Defaults to FALSE.

...

Not used

Value

Matrix: First column, lower bound; second column, upper bound.