[R] predict.coxph and predict.survreg
ahnven at gmail.com
Thu Nov 11 17:03:37 CET 2010
Indeed, from the predict() function of the coxph you cannot get
directly "time" predictions, but only linear and exponential risk
scores. This is because, in order to get the time, a baseline hazard
has to be computed and it is not straightforward since it is implicit
in the Cox model.
2010/11/11 David Winsemius <dwinsemius at comcast.net>:
> On Nov 11, 2010, at 3:44 AM, Michael Haenlein wrote:
>> Dear all,
>> I'm struggling with predicting "expected time until death" for a coxph and
>> survreg model.
>> I have two datasets. Dataset 1 includes a certain number of people for
>> I know a vector of covariates (age, gender, etc.) and their event times
>> (i.e., I know whether they have died and when if death occurred prior to
>> end of the observation period). Dataset 2 includes another set of people
>> which I only have the covariate vector. I would like to use Dataset 1 to
>> calibrate either a coxph or survreg model and then use this model to
>> determine an "expected time until death" for the individuals in Dataset 2.
>> For example, I would like to know when a person in Dataset 2 will die,
>> his/ her age and gender.
>> I checked predict.coxph and predict.survreg as well as the document "A
>> Package for Survival Analysis in S" written by Terry M. Therneau but I
>> to admit that I'm a bit lost here.
> The first step would be creating a Surv-object, followed by running a
> regression that created a coxph-object, using dataset1 as input. So you
> should be looking at:
> There are worked examples in the help pages. You would then run predict() on
> the coxph fit with "dataset2" as the newdata argument. The default output is
> the linear predictor for the log-hazard relative to a mean survival estimate
> but other sorts of estimates are possible. The survfit function provides
> survival curve suitable for plotting.
> (You may want to inquire at a local medical school to find statisticians who
> have experience with this approach. This is ordinary biostatistics these
>> Could anyone give me some advice on how this could be done?
>> Thanks very much in advance,
>> Michael Haenlein
>> Professor of Marketing
>> ESCP Europe
>> Paris, France
> David Winsemius, MD
> West Hartford, CT
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