R help - Aug 2009 - C-statistic comparison with partially paired datasets

Does anyone know of an R-function or method to compare two C-statistics 
(Harrells's C - rcorr.cens) obtained from 2 different models in 
partially paired datasets (i.e. some similar and some different cases), 
with one continuous independent variable in each separate model? (in a 
survival analysis context)?
I have noticed that the rcorrp.cens function can be used for paired data.
   
Thanks for any help,

Hanneke Wijnhoven

-- 
Hanneke A.H. Wijnhoven (PhD) 
Institute of Health Sciences 
Vrije Universiteit Amsterdam 
De Boelelaan 1085 
1081 HV Amsterdam 
The Netherlands 
Tel. +31 (0) 20 5989951 
Fax. +31 (0) 20 5986940 
hanneke.wijnhoven at falw.vu.nl

Hanneke Wijnhoven wrote:
> Does anyone know of an R-function or method to compare two C-statistics 
> (Harrells's C - rcorr.cens) obtained from 2 different models in 
> partially paired datasets (i.e. some similar and some different cases), 
> with one continuous independent variable in each separate model? (in a 
> survival analysis context)?
> I have noticed that the rcorrp.cens function can be used for paired data.
>   Thanks for any help,
> 
> Hanneke Wijnhoven
> 
Hanneke,

I'm having trouble seeing how the unpaired observations can contribute 
information in general.  If for example all of the observations were 
unpaired, one C-statistic might be larger because it came from a dataset 
with more extreme observations that were easier to discriminate.

Frank

-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University