[R] survival::survfit,plot.survfit

[Bernhard Reinhardt]

You are right. In my case it doesn´t make much difference since the mean 
of my covariates is about 0.

I made some more plots and again I´m confused. I thought when forcing 
all covariates via the newdata  argument to be zero I would get the 
baseline function since the "linear predictor" is then zero, too.

As I pointed out in another post I´m trying out models with different 
number of covariates on the same data. For example I use a model with 
only one covariate. The mean of this covariate is 0.01. So the curves of

surv <- survfit(coxsst4_full)
and

attach(nino4)
newS4 <- data.frame(S5=0.)
detach()
new_surv <- survfit(coxsst4, newdata=newS4)

differ very slightly.

Of course also the mean curves for models with more then one covariate 
differe slightly from the "Zero"-curve.

BUT shouldn´t the "Zero"-curves for all models be the same?

#Two models
coxsst4 <- coxph(Surv(schaeden)~ S5, data=nino4)
coxsst4_full  <- coxph(Surv(schaeden)~ 0+S1+S2+S3+S4+S5+S6+S7+S8+S9+S10, 
data=nino4)

#Set all covariates 0
attach(nino4)
newS4 <- data.frame(S0=0., S1=0., S2=0., S3=0., S4=0., S5=0., S6=0., 
S7=0., S8=0., S9=0., S10=0.)
detach()

new_surv1 <- survfit(coxsst4, newdata=newS4)
new_surv2 <- survfit(coxsst4_full, newdata=newS4)

Yields two different curves. What did I get wrong?

Regards

Bernhard


Terry Therneau wrote:

>> plot(survfit(fit)) should plot the survival-function for x=0 or 
>> equivalently beta'=0. This curve is independent of any covariates.
> 
>   This is not correct.  It plots the curve for a hypothetical subject with x= 
> mean of each covariate.  
>   This is NOT the "average survival" of the data set.  Imagine a cohort made up 
> of 60 year old men and their 10 year old grandsons: the expected survival of 
> this cohort does not look that for a 35 year old male.
>   
>   	Terry T
>