| Literature DB >> 30799913 |
Huazhen Lin1, Xiao-Hua Zhou2,3,4, Gang Li5.
Abstract
In this article, we study a direct receiver operating characteristic (ROC) curve regression model with completely unknown link and baseline functions. A semiparametric procedure is proposed to estimate both the parametric and non-parametric components of the model. The resulting parameter estimates and ROC curve estimates are shown to be consistent and asymptotically normal with a n -1/2 convergence rate. With arbitrary link and baseline functions, our model is more robust than existing direct ROC regression models that require either complete or partially complete specification of the link and baseline functions. Moreover, the robustness of our new method is gained at little cost to efficiency, as evidenced by the parametric convergence rate of our estimators and by the simulation study. An illustrative example is given using a hearing test data set.Entities:
Keywords: Diagnostic tests; ROC regression; kernel smoothing; nonparametric; transformation models
Year: 2012 PMID: 30799913 PMCID: PMC6385595 DOI: 10.5705/ss.2010.167
Source DB: PubMed Journal: Stat Sin ISSN: 1017-0405 Impact factor: 1.261