Robustness of approaches to ROC curve modeling under misspecification of the underlying probability model Journal Article
| Authors: | Devlin, S. M.; Thomas, E. G.; Emerson, S. S. |
| Article Title: | Robustness of approaches to ROC curve modeling under misspecification of the underlying probability model |
| Abstract: | A variety of statistical regression models have been proposed for the comparison of ROC curves for different markers across covariate groups. Pepe developed parametric models for the ROC curve that induce a semiparametric model for the market distributions to relax the strong assumptions in fully parametric models. We investigate the analysis of the power ROC curve using these ROC-GLM models compared to the parametric exponential model and the estimating equations derived from the usual partial likelihood methods in time-to-event analyses. In exploring the robustness to violations of distributional assumptions, we find that the ROC-GLM provides an extra measure of robustness. Copyright © Taylor & Francis Group, LLC. |
| Keywords: | statistics; models; model misspecification; estimating equations; roc curves; roc curve regression; semiparametric models; partial likelihood methods; probability modeling; semi-parametric modeling; statistical regression model; mathematical techniques |
| Journal Title: | Communications in Statistics - Theory and Methods |
| Volume: | 42 |
| Issue: | 20 |
| ISSN: | 0361-0926 |
| Publisher: | Taylor & Francis Group |
| Date Published: | 2013-01-01 |
| Start Page: | 3655 |
| End Page: | 3664 |
| Language: | English |
| DOI: | 10.1080/03610926.2011.636166 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | --- - "Export Date: 1 October 2013" - "CODEN: CSTMD" - "Source: Scopus" |
