On Apr 18, 2011, at 4:09 PM, array chip wrote:
Sorry this is a re-post. I posted it last night, haven't heard from
anyone, hope
this moves the thread up a little and anyone can comment?
My observation is that coefficients of 19 in Cox (or other exponential
models) models generally indicate numerical difficulties rather than
correct estimates.
--
David.
Thanks!
John
----- Forwarded Message ----
From: array chip <arrayprof...@yahoo.com>
To: r-help@r-project.org
Sent: Sun, April 17, 2011 11:33:32 PM
Subject: time dependent hazard ratios
Hi, I am new to time-dependent Cox model to estimate time dependent
hazard
ratios. Let me use aml dataset from survival package as an example:
aml3<-survSplit(aml,cut=c(5,10,20),end="time",start="start",
event="status",episode="i")
This will generate the new data frame based on the time cut points
5, 10 and 20
and produce a indicator variable "i" that indicates the time
interval membership
for each observation.
If I want to esimate hazard ratio of variable "x" (Nonmaintained vs
Maintained)
for each of the time intervals 0-5, 5-10, 10-20 and >=20, would the
following
calculate such HRs?
coxph(Surv(start,time,status)~x*as.factor(i),data=aml3)
Call:
coxph(formula = Surv(start, time, status) ~ x * as.factor(i),
data = aml3)
coef exp(coef) se(coef) z p
xNonmaintained 19.2 2.10e+08 10461 0.00183 1
as.factor(i)1 NA NA 0 NA NA
as.factor(i)2 NA NA 0 NA NA
as.factor(i)3 NA NA 0 NA NA
xNonmaintained:as.factor(i)1 -18.3 1.17e-08 10461 -0.00175 1
xNonmaintained:as.factor(i)2 -19.6 3.18e-09 10461 -0.00187 1
xNonmaintained:as.factor(i)3 -18.0 1.46e-08 10461 -0.00172 1
So my understanding is that:
for time interval 0-5, HR=exp(19.2)=2.1e+08
for time interval 5-10, HR=exp(19.2-18.3)=2.46
for time interval 10-20, HR=exp(19.2-19.6)=0.67
for time interval >=20, HR=exp(19.2-18.0)=3.32
Am I correct on estimating these time dependent HRs?
Thanks
John
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