Question 1: How to get just 2 cumulative incidence curves when there are
multiple covariates.
I don't understand what you want. Assume that we have "liver transplant" and "death
while waiting for a transplant" as my two events. There are overall curves (2), or one
can create curves separately for each sex, or for different institutions. What do you
mean by "a curve for age"?
If you want competing risks after Cox model adjustment, see the mstate
package.
Question 2: "mine" data. There is no such data. This was a hypthetical example in the
document, and I chose a poor name for the data set; "your_data_set" would have been
better. I was using "mine" in the sense of "this data set is mine, it belongs to me", and
now see that it could confuse someone. The file sourcecode.pdf is intended to document
the computational algorithms, but not how a user would approach the function. A vignette
is planned, someday...
Terry Therneau
On 12/30/2013 04:04 PM, Jieyue Li wrote:
Dear All,
I want to have the cumulative incidence curves for 'mstate' data using Survival
package in
R. But I got some problems:
I. Problem 1:
1. If I only use intercept without any covariates, I can have 'right'
cumulative incidence
curves (2 for 2 competing risks):
library(Survival)
fitCI <- survfit(Surv(stop, status*as.numeric(event), type="mstate") ~
1,data=mgus1,
subset=(start==0))
plot(fitCI)
2. If I include one variate ('sex'), I get 4 curves (attached; I guess because
there are
two levels in 'sex' and 2 competing risks):
fitCI <- survfit(Surv(stop, status*as.numeric(event), type="mstate")
~sex,data=mgus1,
subset=(start==0))
plot(fitCI)
However, I want to just have 2 cumulative incidence curves estimated from
several
covariates (such as 'sex', 'age', 'alb', etc. in mgus1). Could you please help
me to do
that? Thank you very much!
II. Problem 2:
I try using an example from sourcecode.pdf:
fit <- survfit(Surv(time, status, type=’mstate’) ~ sex, data=mine)
but where can I have the 'mine' data? Thank you!
Best,
Jieyue
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