[R] C-statistic comparison with partially paired datasets

[Hanneke Wijnhoven]

Frank,

Thank you for your quick response!

I want to compare the discriminative capacity of different 
anthropometric measures in predicting mortality, focussing on the "thin" 
site of these measures.
Since these associations are not linear (U shaped for BMI and inversily 
J-shaped for mid-upper arm circumference) and I do not want to include 
the prediction by "obesity", I am using all values below the median of 
each separate measure to calculate a C-statistic (below the median, the 
association is approximately linear).
As a result, some different and some overlapping cases are included.
I understand your point though.

Any suggestion is welcome.

Hanneke

Frank E Harrell Jr schreef:
> 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
>


-- 
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