The solution is to use a separate function to do this (and call it from the
print method).
On Mon, 8 May 2006, Heinz Tuechler wrote:
At 12:55 07.05.2006 +0100, Prof Brian Ripley wrote:
On Sun, 7 May 2006, Heinz Tuechler wrote:
Hello Xiaochun Li!
Thank you for submitting the function. At the time I had that problem I
solved it in a somewhat different way.
I changed a few lines in the print.survfit method. I introduced a parameter
"ret.res=FALSE" set to false to preserve the normal behaviour of print.
The second last line "invisible(x)" I changed to:
if (ret.res)
invisible(list(x,x1))
else
invisible(x)
So print.survfit returned the results. Of course, Your method has the
advantage to work as long as the output structure of print.survfit does not
change. At the end I would prefer the original function to be changed and
when I find the time I will submit a worked proposal to Thomas Lumley, the
maintainer of the survival package. In that way it would be available also
in future versions of survival.
But all print() methods are required to return their first argument
unchanged, so
foo
print(foo)
do the same thing. See ?print.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
I see that my proposal is against the rules.
So what would be a correct solution? Using the (expanded) example from
Xiaochun Li, you see that print(fit1) does not _simply_ print its first
argument, but calculates the median and its confidence interval.
What would be the correct way to access these values?
# example:
library(survival)
fit1 <- survfit(Surv(time, status) ~ 1, data=aml)
print(fit1)
Call: survfit(formula = Surv(time, status) ~ 1, data = aml)
n events median 0.95LCL 0.95UCL
23 18 27 18 45
smed <- function(x) {
ox <- capture.output(print(x))
n <- length(ox)
tmp <- t(sapply(ox[4:n],
function(l) strsplit(l, split=' +')[[1]]))
nres <- strsplit(ox[3],split=' +')[[1]][2:6]
res <- matrix(as.numeric(tmp[,2:6]), ncol=5,
dimnames=list(tmp[,1], nres))
res
}
sf1 <- smed(fit1)
sf1
Lacking experience in R-programming, my personal opinion is that
calculations like the median and the confidence interval should not be only
side effects of a print command but accessible result objects of a
corresponding function.
Heinz Tüchler
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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