[R] C-statistic comparison with partially paired datasets
Frank E Harrell Jr
f.harrell at vanderbilt.edu
Thu Aug 13 14:00:49 CEST 2009
Hanneke Wijnhoven wrote:
> 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.
Subsetting the data will make the two task difficulties unequal, I fear.
This would make it difficult to compare predictive discrimination indexes.
I think it would be better to fit splines to the continuous predictors,
to allow for a unified analysis over the whole range. Then everything
> 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
>>> Thanks for any help,
>>> Hanneke Wijnhoven
>> 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 E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
More information about the R-help