From: Calum <stats_at_wittongilbert.free-online.co.uk>

Date: Mon, 03 Mar 2008 09:16:05 +0000

R-help_at_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. Received on Mon 03 Mar 2008 - 09:25:51 GMT

Date: Mon, 03 Mar 2008 09:16:05 +0000

*> 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,
**>> dist='weibull')
*

Peter wrote:

> I'd take a hard look at the pweibull(...) bit. Is "scale" really what

*> you want it to be? If coef(my_curve.Pred) is not a scalar, then it gets
**> recycled, which could easily cause oscillations.
*

Aha - found it. Its from my attempt to subgroup the data before I discovered subset... I now have a curve instead of an oscillation. Now possibly that curve is wrong... will need to do more reading!

For reference the line above should read:

> my_curve.Plac <- survreg( Surv(Survival, Censored==0)~ 1, subset=TreatmentGroup=="Placebo", data=TestData, dist='weibull')

>> 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?
**>>
**> Customarily they are not. (I'm sure it is possible to speculate at
**> length about it, though.)
**>
*

Going off topic a bit - but did you mean customarily they are not
censored or customarily they are not handled differently from censored!

> Nothing spectacularly incompetent this far... (I'm not happy with R^2

*> measures outside of linear models, or even within linear models, but
**> several well-reputed people do find them useful, so who am I to bicker?)
*

I'm not competent to argue. But are you suggesting there is a better way to assess fit of the line to the data? Thats what I want - Not being a statistician I'm not fussed how its done. But If I'm going to extrapolate a line I'd like to know its a reasonable fit first (is that purely by eye?) There is a p value reported by survreg but no idea how to interpret it ;-)

R-help_at_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. Received on Mon 03 Mar 2008 - 09:25:51 GMT

Archive maintained by Robert King, hosted by
the discipline of
statistics at the
University of Newcastle,
Australia.

Archive generated by hypermail 2.2.0, at Mon 03 Mar 2008 - 14:30:18 GMT.

*
Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help.
Please read the posting
guide before posting to the list.
*