require(boot)
    # relative yield takes a matrix or dataframe and finds the ratio
    # of the means: treatmentMean/controlMean.
    # data structure:
    # first column is strata, control = 1 and treatment = 2
    # second column is response, or the data to be bootstrapped
    rel.yield <- function(D,i) {
      trt <- D[i,1]
      resp <- D[i,2]
      mean(resp[trt==2]) / mean(resp[trt==1])
    }

    # some data that has a true rel.yield of 10
    sub.pop <- matrix(data = c(rep(1,15),rep(2,15),rnorm(15,2,1),rnorm(15,20,1)),
                      nrow = 30, ncol = 2, dimnames = list((1:30),c('trt','resp')))

    # with strata specified
    b <- boot(sub.pop, rel.yield, R = 1000, strata = sub.pop[,1])
    #without strata specified
    c <- boot(sub.pop, rel.yield, R = 1000)

    # note the distributions of t* are similar
    par(mfrow=c(1,2))
    hist(b$t)
    abline(v=mean(b$t))
    hist(c$t)
    abline(v=mean(c$t))

    # and the CI estimates are also similar
    boot.ci(b)
    boot.ci(c)