Question is regarding the roc function of pROC package.
Package link: https://www.rdocumentation.org/packages/pROC/versions/1.18.5/topics/roc. Paper link https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3068975/.

I am plotting confidence intervals on my ROC plot:

pROC::roc(as.factor(df$classes),
                   df$score ,
                   plot=TRUE,
                   ci = TRUE,
                   ci.method= 'bootstrap',
                   auc.polygon=TRUE,
                   max.auc.polygon=TRUE,
                   print.auc=TRUE)

I understand from documentation that when using the ci.method as ‘bootstrap’, stratified bootstrapping takes place. How to find the subsampling percentage used while bootstrapping? Is it 80% of total data, 70% or something else? Can we specify it?

The paper quotes, “Bootstrap is stratified by default; in this case the same number of case and control observations than in the original sample will be selected in each bootstrap replicate.”. I think they meant same proportion of case and control observations in each replicate. However, what percentage of subsampling takes place is not mentioned anywhere.

If I am interpretting it wrong please correct me.