[R] Predictions from "coxph" or "cph" objects

[David Winsemius]

On Jul 5, 2014, at 12:43 PM, Axel Urbiz wrote:

> Thank you David. It is my understanding that using survfirsurvit  
> below I get the median predicted survival. I actually was looking  
> for the mean. I can't seem to find in the documentation how to get  
> that.
>
> options(na.action=na.exclude) # retain NA in predictions
> fit <- coxph(Surv(time, status) ~ age + ph.ecog, lung)
> pred <- survfit(fit, newdata=lung)
> head(pred)
>
There might be a way. I don't know it if so, so I would probably just  
use the definition of the mean:

sum(summary(pred)$surv* summary(pred)$time)/sum(  summary(pred)$time)

(I continue to take effort to keep my postings in plain text despite  
my mail-clients's efforts to match your formatted postings. It adds to  
the work of responders when you post formatted questions and responses.)


> Thanks again,
> Axel.
>
>
>
> On Sat, Jul 5, 2014 at 1:54 PM, David Winsemius <dwinsemius at comcast.net 
> > wrote:
>
> On Jul 5, 2014, at 5:28 AM, Axel Urbiz wrote:
>
> Dear R users,
>
> My apologies for the simple question, as I'm starting to learn the  
> concepts
> behind the Cox PH model. I was just experimenting with the survival  
> and rms
> packages for this.
>
> I'm simply trying to obtain the expected survival time (as opposed  
> to the
> probability of survival at a given time t).
>
> What does "expected survival time" actually mean? Do you want the  
> median survival time?
>
>
> I can't seem to find an option
> from the "type" argument in the predict methods from coxph{survival}  
> or
> cph{rms} that will give me expected survival times.
>
> library(rms)
> options(na.action=na.exclude) # retain NA in predictions
> fit <- coxph(Surv(time, status) ~ age + ph.ecog, lung)
> fit2 <-  cph(Surv(time, status) ~ age + ph.ecog, lung)
> head(predict(fit,type="lp"))
> head(predict(fit2,type="lp"))
>
> `predict` will return the results of the regression, i.e. the log- 
> hazard ratios for each term in the RHS of the formula. What you want  
> (as described in the Index for the survival package) is either  
> `survfit` or `survexp`.
>
> require(survival)
> help(pack=survival)
> ?survfit
> ?survexp
> ?summary.survfit
> ?quantile.survfit   # to get the median
> ?print.summary.survfit
>
> require(rms)
> help(pack=rms)
>
> The rms-package also adds a `survfit.cph` function but I have found  
> the `survest` function also provides useful added features, beyond  
> those offered by survfit
>
>
>
> Thank you.
>
> Regards,
> Axel.
>
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> -- 
>
> David Winsemius, MD
> Alameda, CA, USA
>
>

David Winsemius, MD
Alameda, CA, USA