[R] A question about external time-dependent covariates in co x model
Hanke, Alex
HankeA at mar.dfo-mpo.gc.ca
Thu Aug 19 14:36:22 CEST 2004
Dear Rui,
>From my understanding of time-dependent covariates (not an expert but have
been working on a similar problem), it would appear that the coding of the
status column is not correct. Unless you have observed an event at each
interval you should only have status=1 for the last interval. In your
example I see 3 in total. Also, I think that if "end" is proportional to
your "covariate" you are incorporating a redundant time effect into the
model. The time effect is in the baseline hazard.
Alex
-----Original Message-----
From: Rui Song [mailto:rsong at stat.wisc.edu]
Sent: August 19, 2004 12:21 AM
To: r-help at stat.math.ethz.ch
Subject: [R] A question about external time-dependent covariates in cox
model
Dear Sir or Madam:
I am a graduate student in UW-Madison statistics department. I have a
question about fitting a cox model with external time-dependent
covariates.
Say the original data is in the following format:
Obs Eventtime Status Cov(time=5) Cov(time=8) Cov(time=10) Cov(time=12)
1 5 1 2
2 8 0(censored) 2 4
3 10 1 2 4 6
4 12 1 2 4 6 8
....
Notice that the time-dependent covariates are identical at the same
time points for all obs since they are external to the failure process.
process.
Then I organized the data as the following:
obs start end eventtime status cov
1 0 5 5 1 2
2 0 5 8 0 2
2 5 8 8 0 4
3 0 5 10 1 2
3 5 8 10 1 4
3 8 10 10 1 6
4 0 5 12 1 2
4 5 8 12 1 4
4 8 10 12 1 6
4 10 12 12 1 8
And fit the model using:
fit<-coxph(Surv(start, end, status)~cov);
When I fit the model to my data set (Which has 89 observations and 81
distinct time points, sort of large.), I always got a message that
"Process R segmentation fault (core dumped)". Would you let me know if it
is due to the matrix sigularity in the computation of the partial
likelihood or something else? And how should I fit a cox model with
external time-dependent covariates?
Thanks a lot for your time and help!
Sincerely,
Rui Song
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