source("http://192.38.117.59/~linearpredictors/datafiles/readCardiac.R")

## personwise standard deviation of log cardiac output
sds.log <- tapply(log(cardiac$cardout), cardiac$person, function(x)(sqrt(var(x, na.rm = T))))

## merging onto whole dataset
cardiac$sd <- sapply(cardiac$person, function(x) sds.log[[x]])

## collapse dataset by using only first row for each person
## should ideally test whether values within persons are indeed equal
collapse <- function(d){
  d[1,] 
}
card <- subset(cardiac, select = -c(cardout, serialno))
card <- lapply(split(card, card$person), collapse)
card <- do.call("rbind",card)

## now the tables:
addmargins(xtabs(~ gender + pacemake, data = card))

with(card,
tapply(sd, list(gender, pacemake), median)
)
## marginal medians
with(card,
tapply(sd, gender, median)
)
with(card,
tapply(sd, pacemake, median)
)
## overall median
median(card$sd)