R help - Aug 2005 - covariance matrix under null

Hello

I am fitting a Cox PH model using the function coxph(). Does anyone know how
to obtain the estimate of the covariance matrix under the null hypothesis.
The function coxph.detail() does not seem to be useful for this purpose.

Thanks,
KD.  

 



	[[alternative HTML version deleted]]

Kindly excuse a non-statistician newbie attempting to wrestle with R.

This might be a relatively easy question, but I am trying to perform nls 
regression and plot the fitted function through the data superimposed on 
the raw data. from reading the R-help, Rtips et al, I am only able to do 
that by extracting the parameter values manually and using it to create 
the plot.

Is there an easier way to do this,  (I have ~60 Plots), obtain an r^2,  
and also plot the x axis in the log domain (any attempts I have tried 
have screwed up).

NLS script

fit<- nls(y~-emax*x^h/(ec50^h+x^h),
       data= sample, start=list(emax=4,h=2,ec50=1))

summary(fit)

Thank you all for your help

Lanre Okusanya, Pharm.D.,BCPS
UB/Pfizer Pharmacometrics Fellow
University at Buffalo School of Pharmacy and Pharmaceutical Sciences
237 Cooke Hall
Buffalo, NY 14260
Email: ooo at buffalo.edu
Tel: (716)645-2828 x 275
Fax: (716)645-2886

You will need to tell us of _what_ you want the covariance matrix and what 
you mean by the `null hypothesis':  coxph does estimation, not testing.

If you want the covariance matrix of the parameter estimates, see vcov(), 
which has a coxph method.

On Thu, 25 Aug 2005, Devarajan, Karthik wrote:
>
> Hello
>
> I am fitting a Cox PH model using the function coxph(). Does anyone know
how
> to obtain the estimate of the covariance matrix under the null hypothesis.
> The function coxph.detail() does not seem to be useful for this purpose.
>
> Thanks,
> KD.
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
PLEASE do (no HTML mail, useful subject, please)

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

On Thu, 25 Aug 2005, Devarajan, Karthik wrote:
>
> Hello
>
> I am fitting a Cox PH model using the function coxph(). Does anyone know
how
> to obtain the estimate of the covariance matrix under the null hypothesis.
> The function coxph.detail() does not seem to be useful for this purpose.
>
You can evaluate the second derivative of the partial loglikelihood at any 
specified beta with

   vcov(coxph(formula, data,iter=0, start, init=beta)

eg if you want to get score tests.

 	-thomas

To get nice looking plots you can use trellis plots from the lattice
package.  First you need:

library(lattice)

Then you can define a custom panel function that will overlay the
fitted curve on top of the data points in a different color (you just
need to do this once; the fit you want plotted is specified as an
argument):

pred.overlay.panel <- function(x, y, fit, ...)
{
   panel.grid()
   panel.xyplot(x, y, ...)
   form <- as.list(sys.call(-2))[[2]]$call$formula
   resp <- deparse(form[[2]])
   covar <- deparse(form[[3]])
   xx <- seq(min(x), max(x), len=101)
   newdat <- data.frame(xx)
   colnames(newdat) <- covar
   panel.superpose(xx, predict(fit, newdata=newdat),
       subscripts=1:length(xx), groups=factor(rep(2, length(xx)),
       levels=1:2), type="l", ...)
}

Finally, you use the custom panel function in a call to xyplot:

xyplot(y ~ x, data=sample, panel=pred.overlay.panel, fit=fit,
scales=list(x=list(log=TRUE)))


Note how you specify that you want the x-axis to be in log-scale with
the scales parameter.

Hope this helps.

Ben

On 8/26/05, Lanre Okusanya <ooo at buffalo.edu>
wrote:
> Kindly excuse a non-statistician newbie attempting to wrestle with R.
> 
> This might be a relatively easy question, but I am trying to perform nls
> regression and plot the fitted function through the data superimposed on
> the raw data. from reading the R-help, Rtips et al, I am only able to do
> that by extracting the parameter values manually and using it to create
> the plot.
> 
> Is there an easier way to do this,  (I have ~60 Plots), obtain an r^2,
> and also plot the x axis in the log domain (any attempts I have tried
> have screwed up).
> 
> NLS script
> 
> fit<- nls(y~-emax*x^h/(ec50^h+x^h),
>        data= sample, start=list(emax=4,h=2,ec50=1))
> 
> summary(fit)
> 
> Thank you all for your help
> 
> Lanre Okusanya, Pharm.D.,BCPS
> UB/Pfizer Pharmacometrics Fellow
> University at Buffalo School of Pharmacy and Pharmaceutical Sciences
> 237 Cooke Hall
> Buffalo, NY 14260
> Email: ooo at buffalo.edu
> Tel: (716)645-2828 x 275
> Fax: (716)645-2886
> 
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
>