I'm implementing a custom bootstrap resampling procedure in R. This procedure resamples clusters of data points obtained by different subjects in an experiment. Since the bootstrap samples need to have the same size as the original dataset, `target.set.size`, I select speakers compute their data point contributions to make sure I have a set of the right size.

    set.seed(1)
    target.sample.size = 1742
    count.lookup = rbind(levels(data$subj), as.numeric(table(data$subj)))

To this end, I create a dynamic list of resampled subjects, `sample.subjects`, that keep on being selected and appended to the list as long as their summed data point contributions do not exceed `target.set.size`. To conveniently retrieve the number of data points that a given subject contributes I constructed a reference matrix, `count.lookup`, where the first row contains subject codes and the second row contains their respective data point counts.

    > count.lookup

    [,1]  [,2]  [,3]  [,4]  [,5]
    [1,] "5"   "6"   "13"  "18"  "20"
    [2,] "337" "202" "311" "740" "152"

This is how the resampling works:

    for (iter in 1:1000){

      #select first subject
      #empty list overwrites sample subjects from previous iteration
      sample.subjects = list()
sample.subjects[1] = sample(unique(data$subj), 1, replace=TRUE, prob=NULL)

      #determine subject position in data point count lookup
first.subj.pos = which(count.lookup[1,]==sample.subjects, arr.ind=TRUE)

      #add contribution of first subject to data point count
      sample.size = as.numeric(count.lookup[2,first.subj.pos])

      #select subject clusters until you exceed target sample size
      while(sample.size < target.sample.size){

        #add another subject
current.subject = sample(unique(data$subj), 1, replace=TRUE, prob=NULL)
        sample.subjects[length(sample.subjects)+1] = current.subject

        #determine subject's position in data point lookup
curr.subj.pos = which(count.lookup[1,]==current.subject, arr.ind=TRUE)

        #add subject contribution to the data point count
sample.size = sample.size + as.numeric(count.lookup[2,curr.subj.pos])
      }

#initialize intermediate data frame; intermediate because it will be shortened to fit target size
      inter.set = data.frame(matrix(, nrow = 0, ncol = ncol(data)))

      #build the bootstrap sample from the selected subjects
      for(j in 1:length(sample.subjects)){

inter.set = rbind(inter.set, data[data$subj == sample.subjects[j],])

      }

      #procustean bed of target sample size
      final.set = inter.set[1:target.sample.size,]

write.csv(final.set, paste("bootstrap_sample_", iter,".csv", sep=""), row.names=FALSE)
      cat("Bootstrap Iteration", iter, "completed\n")

      #clean up sample.size for next bootstrap iteration
      sample.size = 0

    }

My problem is that when I sample the second subject onward and add it to `sample.subjects` (regardless of whether it is a list of a vector), what actually gets added to `sample.subjects` seems to be the index of that subject in `count.lookup`! When I select the first subject code and create a list consisting of just that subject code as the only element, everything is fine.

> sample.subjects[1] = sample(unique(tt1$subj), 1, replace=TRUE, prob=NULL)
    > sample.subjects
    [[1]]
    [1] 5

I know this is the actual subject number because when I check the number of data points that this subject contributes in `count.lookup`, it is the number that corresponds to subject 5.

    > sample.size = as.numeric(tt1.lookup[2,first.subj.pos])
    > sample.size

However, when I append further sampled subject codes to the list, for some reason they surface as their index number in count.lookup.

    > sample.subjects
    [[1]]
    [1] 5

    [[2]]
    [1] 5

    [[3]]
    [1] 1

    [[4]]
    [1] 2

    [[5]]
    [1] 5

    [[6]]
    [1] 2

    [[7]]
    [1] 2

    [[8]]
    [1] 3

    [[9]]
    [1] 3

The third element, for example, is 1. This coincides with none of the subject codes in count.lookup.

It seems the problem lies in how I append to `sample.subjects`. I tried both vectors and list as data structures in which to store sampled subject codes. For each data type, I tried two ways of appending: the one I present above, and one that is more idiomatic in R:

sampled.subjects = [current.subject, sampled.subjects] (for lists)

and

sampled.subjects = c(current.subject, sampled.subjects) (for vectors)

Are these appending strategies flawed here or is there some stupid error I'm making somewhere else that is making the indices to surface instead of subject codes?

I'd appreciate all your help!

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