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