Frank, thank you very much for your answer. Yes, I also estimated splines like you suggested but wanted to add "more custom" analyses as well. Your answer does help me however, thanks. Hanneke
> Hanneke Wijnhoven wrote: >> 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 > > 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 > is paired. > > Frank > >> >> 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 >>> >> >> > > > -- > Frank E Harrell Jr Professor and Chair School of Medicine > Department of Biostatistics Vanderbilt University > ______________________________________________ R-help@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.