Accommodating covariates roc analysis screenupdating vba msdn

In this paper, we obtain one single objective function with the group SCAD to select grouped variables, which adapts to popular criteria of model selection, and propose a two-stage framework to apply the focused information criterion (FIC).

Some asymptotic properties of the proposed methods are derived.

Regression models are introduced into the receiver operating characteristic (ROC) analysis to accommodate effects of covariates, such as genes.

If many covariates are available, the variable selection issue arises.

These methods follow naturally when representing the ROC curve as a summary of the distribution of case marker observations, standardized with respect to the control distribution.The proposed model is applied to data concerning diagnosis of diabetes. uses cookies to improve performance by remembering your session ID when you navigate from page to page. Please set your browser to accept cookies to continue.This cookie stores just a session ID; no other information is captured.

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