df <-data.frame(
              modality=rep(c("A","B"),each=25,2),
              reader=rep(c("reader1","reader2"),each=50),
              case= rep(c("1","2","3","4","5"),each=5,2),
              area=rep(c("a1","a2","a3","a4","a5"),20),
              score=sample(1:5,100, replace=TRUE),
              disease=rep(sample(0:1,25, replace=TRUE),4),
              stringsAsFactors=FALSE)

> df
    modality  reader case  area score disease
1          A reader1    1   a1     5       0
2          A reader1    1   a2     3       0
3          A reader1    1   a3     4       1
4          A reader1    1   a4     2       0
5          A reader1    1   a5     5       1
6          A reader1    2   a1     1       1
7          A reader1    2   a2     3       1

# dplyr
library(dplyr)

replicate(100, {
  cluster_sample <- data.frame(case= sample(df$case, replace = TRUE))
  dat_sample <- df %>% inner_join(cluster_sample, by = "case")
  dat_sample
})

library(pROC)
roc1 <- roc(df[which(df$reader=="reader1"&df$modality=="A"),]$disease, df[which(df$reader=="reader1"&df$modality=="A"),]$score)
roc1 <- roc(df[which(df$reader=="reader2"&df$modality=="A"),]$disease, df[which(df$reader=="reader2"&df$modality=="A"),]$score)
rocm <- multiclass.roc(df[which(df$modality=="A"),]$disease, df[which(df$modality=="A"),]$score)