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ORDINAL REGRESSION METHODOLOGY FOR ROC CURVES DERIVED FROM CORRELATED DATA
Author(s) -
TOLEDANO ALICIA Y.,
GATSONIS CONSTANTINE
Publication year - 1996
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/(sici)1097-0258(19960830)15:16<1807::aid-sim333>3.0.co;2-u
Subject(s) - ordinal data , ordinal regression , regression analysis , statistics , regression , receiver operating characteristic , computer science , linear regression , data mining , mathematics
We present an approach for the analysis of correlated ROC data, using ordinal regression models in conjunction with generalized estimating equations. The approach applies to the analysis of degree‐of‐suspicion data derived from multiple interpretations of the same diagnostic study and from the examination of the same patients with multiple diagnostic modalities. The regression models make it possible to incorporate patient and reader characteristics into the analysis, without having to resort to stratification. We illustrate the potential of the approach with analysis of data from two studies in diagnostic oncology.