bootstrapping respecting subject level information

Hi there,

This is the first time I use this forum, and I want to say from the start I am not a skilled programmer. So please let me know if the question or code were unclear!

I am trying to bootstrap an interaction (that is my test statistic) using the package "boot". My problem is that for every resample, I would like the randomization to be done within subjects, so that observations from different subjects are not mixed. Here is the code to generate a dataframe similar to mine:

Subject = rep(c("S1","S2","S3","S4"),4)
Num     = rep(c("singular","plural"),8)
Gram    = rep(c("gram","gram","ungram","ungram"),4)
RT      = c(657,775,678,895,887,235,645,916,930,768,890,1016,590,978,450,920)
data    = data.frame(Subject,Num,Gram,RT)

This is the code I used to get the empirical interaction value:

summary(lm(RT ~ Num*Gram, data=data))

As you can see, the interaction between my two factors is -348. I want to get a bootstrap confidence interval for this statistic, which I can generate using the "boot" package:

#Function to create the statistic to be boostrapped
boot.huber <- function(data, indices) {
data <- data[indices, ] #select obs. in bootstrap sample
mod <- lm(RT ~ Num*Gram, data=data)
coefficients(mod)       #return coefficient vector
}

#Generate bootstrap estimate
data.boot <- boot(data, boot.huber, 1999)

#Get confidence interval
boot.ci(data.boot, index=4, type=c("norm", "perc", "bca"),conf=0.95) #4 gets the CI for the interaction

My problem is that I think the resamples should be generated without mixing the individual subjects observations: that is, to generate the new resamples, the observations from subject 1 (S1) should be shuffled within subject 1, not mixing them with the observations from subjects 2, etc... I don't know how "boot" is doing the resampling (I read the documentation but don't understand how the function is doing it)

Does anyone know how I could make sure that the resampling procedure used by "boot" respects the subject level information?

Thanks a lot for your help/advice!