> albuterol <- read.table("/group/ftp/pub/kcowles/datasets/albuterl.txt",
+ header = T)

> medstat
function( df, ind)
{
        median( df[ind,"after"] - df[ind,"before"] )
}

> library(boot)
> bootalb.out <- boot( albuterol, medstat, 1999)
> bootalb.out

ORDINARY NONPARAMETRIC BOOTSTRAP


Call:
boot(data = albuterol, statistic = medstat, R = 1999)


Bootstrap Statistics :
    original      bias    std. error
t1*     -1.1 -0.01176588   0.2508711
> boot.ci( bootalb.out)
BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS
Based on 1999 bootstrap replicates

CALL : 
boot.ci(boot.out = bootalb.out)

Intervals : 
Level      Normal              Basic         
95%   (-1.580, -0.597 )   (-1.628, -0.628 )  

Level     Percentile            BCa          
95%   (-1.572, -0.572 )   (-1.798, -0.816 )  
Calculations and Intervals on Original Scale


#The bootstrap unbiased estimate is
#              -1.1 - (-0.01177) = -1.088

#The estimated bias is on the order of 1%, so bias correction probably
# isn't needed.

#The standard error is 0.251.

# The four confidence intervals are given above.

> hist(bootalb.out$t)
> abline( v = bootalb.out$t0 )


#Since all the confidence intervals lie strictly to the left of 0, we
# conclude that albuterol does reduce the work of breathing in the 
#population of interest.