Abstract:
:Most diagnostic accuracy measures and criteria for selecting optimal cut-points are only applicable to diseases with binary or three stages. Currently, there exist two diagnostic measures for diseases with general k stages: the hypervolume under the manifold and the generalized Youden index. While hypervolume under the manifold cannot be used for cut-points selection, generalized Youden index is only defined upon correct classification rates. This paper proposes a new measure named maximum absolute determinant for diseases with k stages ([Formula: see text]). This comprehensive new measure utilizes all the available classification information and serves as a cut-points selection criterion as well. Both the geometric and probabilistic interpretations for the new measure are examined. Power and simulation studies are carried out to investigate its performance as a measure of diagnostic accuracy as well as cut-points selection criterion. A real data set from Alzheimer's Disease Neuroimaging Initiative is analyzed using the proposed maximum absolute determinant.
journal_name
Stat Methods Med Resjournal_title
Statistical methods in medical researchauthors
Dong T,Attwood K,Hutson A,Liu S,Tian Ldoi
10.1177/0962280215611631subject
Has Abstractpub_date
2017-12-01 00:00:00pages
2832-2852issue
6eissn
0962-2802issn
1477-0334pii
0962280215611631journal_volume
26pub_type
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