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#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.
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
At 15:28 26.02.2009, 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.
Does this me
Thanks very much, Bernhard and Terry.
It clarify my confusion and really helps a lot.
Regards
Jeff Xu
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
> 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. Im
Jeff Xu wrote:
I am confused when trying the function survfit.
my question is: what does the survival curve given by plot.survfit mean?
is it the survival curve with different covariates at different points?
or just the baseline survival curve?
for example, I run the following code and get the
I am confused when trying the function survfit.
my question is: what does the survival curve given by plot.survfit mean?
is it the survival curve with different covariates at different points?
or just the baseline survival curve?
for example, I run the following code and get the survival curve
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