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

[David Winsemius]

On Jul 5, 2014, at 9:12 PM, David Winsemius wrote:

>
> 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)
>

Er, I think I meant to type:

fit <- coxph(Surv(time, status) ~ age + ph.ecog, lung)
pred <- survfit(fit)

  sum(summary(pred)$surv* summary(pred)$time)/sum(  summary(pred)$surv)
[1] 211.0943


> (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.
>>
>>        [[alternative HTML version deleted]]
>>
>> This is a plain text mailing list.
>>
>> -- 
>>
>> David Winsemius, MD
>> Alameda, CA, USA
>>
>>
>
> David Winsemius, MD
> Alameda, CA, USA
>
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David Winsemius, MD
Alameda, CA, USA