ROC analysis is a standard method for estimating and comparing diagnostic tests' accuracies when the gold standard is binary. However, there are many situations when the gold standard is not binary. In these situations, traditional ROC methods applied have lead to biased and uninformative outcomes. This article introduces nonbinROC, software for R that implements nonparametric estimators proposed by Obuchowski (2005) for estimating and comparing diagnostic tests' accuracies when the gold standard is measured on a continuous, ordinal or nominal scale. The results produced from these estimators are interpreted in the same manner as in ROC analysis but are not associated with any ROC curve.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
file. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.