Dear R list,
How can confidence interval be derived for e.g. the Tau-a coefficient or the c index (area under ROC curve) such that I can compare the fitted lrm (logistic) models with each other. Is this possible?
The aim is to conclude that one model is significantly better than other
model (a, b or c).
y~a (continu)+ d(catergoric) y~b (continu)+ d(catergoric) y~c (continu)+ d(catergoric)
I will look at residual deviance, the AIC, c-index en Tau-a to compare different logistic models (lrm Design package). All extra advice is mostly welcome!
Regards, Jan
You can only do this if you have an independent test dataset that was never used in model development or coefficient estimation. Given that, look at the rcorrp.cens function in Hmisc.
Frank Harrell
_______________________________________________________________________
ir. Jan Verbesselt Research Associate Lab of Geomatics Engineering K.U. Leuven
Vital Decosterstraat 102. B-3000 Leuven Belgium Tel: +32-16-329750 Fax: +32-16-329760
http://gloveg.kuleuven.ac.be/
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Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University______________________________________________ R-help@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
