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Furthermore, in the ROC regression, the accuracy of area under the curve (AUC) should be the focus instead of aiming at the consistency of model selection or the good prediction performance.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).The concept of covariate adjustment is well established in therapeutic and etiologic studies.However, it has received little attention in the growing area of medical research devoted to the development of markers for disease diagnosis, screening, or prognosis, where classification accuracy, rather than association, is of primary interest.This question is about estimating cut-off scores on a multi-dimensional screening questionnaire to predict a binary endpoint, in the presence of correlated scales.I was asked about the interest of controlling for associated subscores when devising cut-off scores on each dimension of a measurement scale (personality traits) which might be used for alcoholism screening.In other words, we would have a cut-off value for IMP where effect of age, gender and anxiety level are removed.

For example, levels of prostate-specific antigen (PSA), a biomarker widely used to screen men for prostate cancer, tend to increase with age.Your access to the NCBI website at gov has been temporarily blocked due to a possible misuse/abuse situation involving your site.This is not an indication of a security issue such as a virus or attack.We usually adjust for other risk factors like gender or age when devising such cut-off (using ROC curve analysis).Now, what about adjusting impulsivity (IMP) on gender, age, and sensation seeking (SS) since SS is known to correlate with IMP?

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