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Semiparametric separation curve approaches for comparing correlated ROC data
【2016.3.7 3:00pm, S309】

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 2016-3-1 

  Colloquia & Seminars 

  Speaker

Prof. Liansheng Tang,George Mason University, USA

  Title

Semiparametric separation curve approaches for comparing correlated ROC data

  Time

2016.3.7 15:00-16:00

  Venue

S309

  Abstract

In this talk we propose a separation curve method to identify the range of false positive rates for which two ROC curves differ or one ROC curve is superior to the other. Our method is based on a general multivariate ROC curve model, including interaction terms between discrete covariates and false positive rates. It is applicable with most existing ROC curve models. Furthermore, we introduce a semiparametric least squares ROC estimator and apply the estimator to the separation curve method. We derive a sandwich estimator for the covariance matrix of the semiparametric estimator. We illustrate the application of our separation curve method through a real life example.  

  Affiliation

 

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