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2010 ; 30
(4
): 509-17
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Lehmann family of ROC curves
#MMPMID20354227
Gönen M
; Heller G
Med Decis Making
2010[Jul]; 30
(4
): 509-17
PMID20354227
show ga
Receiver operating characteristic (ROC) curves evaluate the discriminatory power
of a continuous marker to predict a binary outcome. The most popular parametric
model for an ROC curve is the binormal model, which assumes that the marker,
after a monotone transformation, is normally distributed conditional on the
outcome. Here, the authors present an alternative to the binormal model based on
the Lehmann family, also known as the proportional hazards specification. The
resulting ROC curve and its functionals (such as the area under the curve and the
sensitivity at a given level of specificity) have simple analytic forms.
Closed-form expressions for the functional estimates and their corresponding
asymptotic variances are derived. This family accommodates the comparison of
multiple markers, covariate adjustments, and clustered data through a regression
formulation. Evaluation of the underlying assumptions, model fitting, and model
selection can be performed using any off-the-shelf proportional hazards
statistical software package.
free
free
free
