Department of Statistics Seminar
North Carolina State University

presents

Dr. Efstathia Bura

George Washington University

"A Model Free Approach To Combining Diagnostic Markers"

ABSTRACT

A popular summary measure of the discriminatory ability of a single continuous diagnostic marker for binary disease outcomes is the receiver-operator characteristics curve (ROC). For most diseases however, single biomarkers do not have adequate sensitivity or specificity for practical purposes. We present an approach to combine several markers into a composite diagnostic test without assuming a model for the distribution of the predictors. Using sufficient dimension reduction techniques, we replace the predictor vector with a lower-dimensional version, obtained through linear transformations of biomarkers, without loss of information. We show how to combine the linear transformations using their asymptotic properties into a scalar diagnostic score whose performance can be assessed by the ROC curve. In the special case that a single linear combination of the markers contains sufficient information for the outcome, this approach results in the same marker combination obtained by Su & Liu (1993) that maximises the area under the ROC curve. The asymptotic distribution of the left singular vectors of a consistent estimate of an asymptotically normally distributed random matrix is derived, which provides the basis for an asymptotic chi-squared test to assess individual biomarker contribution to the diagnostic score.

Friday, March, 17, 2006

3:35 - 4:35 pm

206 Cox Hall

Refreshments will be served on the second floor of Dabney Hall (left of Room 222) at 3:00 pm.