#' Function to compute 0.95 confidence interval for the difference in two means
#'
#' @author TGT
#' @note g is grouping variable
#' @export
# in order to make this work, need to install the Hmisc library(Add Warning?)
# smean.cl.boot: fast implementation of the basic nonparametric bootstrap
# for obtaining confidence limis for the population mean
# without assumming normality.
bootdif <- function(y, g) {
g <- as.factor(g)
# vector of means from 1000 times bootstrapped resampling for each group
a <- attr(smean.cl.boot(y[g==levels(g)[1]], B=1000, reps=TRUE),'reps')
b <- attr(smean.cl.boot(y[g==levels(g)[2]], B=1000, reps=TRUE),'reps')
# get difference of the two groups' means
meandif <- diff(tapply(y, g, mean, na.rm=TRUE))
# get the 95 % confidence limits from bootstrapped resampling
a.b <- quantile(b-a, c(.025,.975))
# result is a vector with value of difference of means and upper and lower limits
res <- c(meandif, a.b)
names(res) <- c('Mean Difference','.025','.975')
res
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.