On Tue, 27 Sep 2005, Maggie Cheang wrote:
Thanks for Terry to reply for my qustion.
Note that it is implicit in Terry's answer that the hazard is smooth.
You have to make some asssumption here, and his includes how smooth it is.
That comes to my second question,
is there a simple way to plot the Hazard ratio from a coxph?
What hazard ratio is that? Note the theory underlying coxph does not
assume that hazards are smooth but that they are very rough.
anyone familiar with the muhaz package?
Yes, and it is discussed (alongside similar ideas) in the MASS on-line
complements. See http://www.stats.ox.ac.uk/pub/MASS4/#Complements .
thanks a bunch
Maggie
On Tuesday, September 27, 2005, at 06:24AM, Terry Therneau <therneau@mayo.edu>
wrote:
The simplest way that I know to get an estimate of the
hazard is to use smoothing splines.
fit <- survfit(Surv(time, status) ~ sex, data=lung)
temp1 <- smooth.spline(fit[1]$time, 1-fit[1]$surv, df=5)
temp2 <- smooth.spline(fit[2]$time, 1-fit[2]$surv, df=5)
plot( predict(temp1, deriv=1), type='l')
lines(predict(temp2, deriv=1), col=2)
------
The lung cancer data set is part of Splus (it's used in several
manual pages as an example). The plot shows the males to have a
higher initial hazard than the females.
You choice of 5 degrees of freedom for the spline was completely
arbitrary.
Terry Therneau
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