Terry Therneau wrote:
>
> It is easier to get survival curves using the predict function. Here is a
> simple example:
>> tfit <- survreg(Surv(time, status) ~ factor(ph.ecog), data=lung)
>> tdata <- data.frame(ph.ecog=factor(0:3))
>> qpred <- predict(tfit, newdata= tdata, type='quantile', p=1:99/
Calum had a long question about drawing survival curves after fitting a Weibull
model, using pweibull, which I have not reproduced.
It is easier to get survival curves using the predict function. Here is a
simple example:
> library(survival)
> tfit <- survreg(Surv(time, status) ~ factor(ph.ecog
Calum wrote:
>>> Also is it possible to get an R-squared type value for the fit of
>>> this curve from someplace?
>>>
>>> Finally (three questions in one!) the first two censored data points
>>> (1 in each group) are actually lost to follow-ups. Should they be
>>> marked differently from censored?
> Calum wrote:
>
>> All of that is very nice so far. The I followed bits and pieces of
>> other peoples posts in the past to plot on a weibull regression...
>>
>> > my_curve.Plac <- survreg( Surv(Survival, Censored==0)~
>> TreatmentGroup, subset=TreatmentGroup=="Placebo", data=TestData,
>>
Calum wrote:
> OK this is bound to be something silly as I'm completely new to R -
> having started using it yesterday. However I am already warming to its
> lack of 'proper' GUI... I like being able to rerun a command by editing
> one parameter easily... try and do that in a Excel Chart Wizzar
OK this is bound to be something silly as I'm completely new to R -
having started using it yesterday. However I am already warming to its
lack of 'proper' GUI... I like being able to rerun a command by editing
one parameter easily... try and do that in a Excel Chart Wizzard!
I eventually want
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