[R] Is there an equivalent to predict(..., type="linear") of a Proportional hazard model for a Cox model instead?
benrhelp at yahoo.co.uk
Fri Nov 26 20:50:34 CET 2010
Hi Terry, David, and Thomas,
Thank you for all your emails and the time you to took to clarify my
misunderstanding on survival analysis. I will need a bit of time to digest all
this information and to do some more reading.
> From: Terry Therneau
> 1. survreg() does NOT fit a proportional hazards model, a mistake
> repeated multiple times in your post
> 2. The coxph function operates on the risk scale: large values of Xbeta
> = large death rates = bad
> The survreg operates on the time scale: large values of xbeta =
> longer liftetime = good.
> 3. predict(fit, type='risk') = exp(predict(fit, type='linear')) in a Cox
> model returns an estimate of the relative risk for each subject. That
> is, his/her predicted death rate as compared to the others in the
> sample. It has no units of "years" or "days" or anything else. The
> predicted survival TIME for a subject is something else entirely.
> predict(fit, type='response') in a survreg model does give predicted
> survvival times.
> If you really want to understand the interrelationships of these
> things more deeply I think you need some textbook time. Read the book
> by Kalbfleisch and Prentice for accelerated failure time models, or even
> better Escobar and Meeker which comes from the industrial reliability
> view. For predicted survival from a Cox model see Chapter 10 of
> Therneau and Grambsch. The answers to your specific questions would be
> a document rather than an email.
> Terry Therneau
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