A combination of Predict (your newdata), cut2, and the plotting function of your choice ought to suffice. But thought that cross-validation was an option. Not at console at the moment (just off airplane.)

Sent from my iPhone

On Aug 15, 2011, at 5:26 PM, array chip <arrayprofile@yahoo.com> wrote:

> is there a R function that produces calibration curve on an independetn data automatically, just like what calibrate() does on the training data itself?
> 
> Thanks
> 
> John
> 
> From: Comcast <dwinsemius@comcast.net>
> To: array chip <arrayprofile@yahoo.com>
> Cc: "r-help@r-project.org" <r-help@r-project.org>
> Sent: Monday, August 15, 2011 2:04 PM
> Subject: Re: [R] calibration curve for cph()
> 
> Build a prediction function using  'Function' that gets applied to set2. Calibrate and validate.
> 
> -- 
> David
> 
> Sent from my iPhone
> 
> On Aug 15, 2011, at 11:31 AM, array chip <arrayprofile@yahoo.com> wrote:
> 
> > Hi, the calibrate.cph() function in rms package generate calibration curve for Cox model on the same dataset where the model was derived using bootstrapping or cross-validation. If I have the model built on dataset 1, and now I want to produce a calibration curve for this model on an independent dataset 2, how can I do that?
> > 
> > Thanks
> > 
> > John
> > 
> >    [[alternative HTML version deleted]]
> > 
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> 
> 

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