[R] cumulative incidence for mstate in Survival package in R
Terry Therneau
therneau at mayo.edu
Tue Dec 31 23:02:41 CET 2013
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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