Semiparametric empirical likelihood confidence intervals for AUC under a density ratio model
| Autor: | Biao Zhang, Suohong Wang |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Statistics and Probability
Statistics::Theory Receiver operating characteristic Applied Mathematics Nonparametric statistics Asymptotic distribution Confidence interval Semiparametric model Computational Mathematics Empirical likelihood Computational Theory and Mathematics Likelihood-ratio test Statistics Econometrics Statistics::Methodology Parametric statistics Mathematics |
| Zdroj: | Computational Statistics & Data Analysis. 70:101-115 |
| ISSN: | 0167-9473 |
| DOI: | 10.1016/j.csda.2013.07.041 |
| Popis: | Inferences on the area under a receiver operating characteristic curve (AUC) are usually based on a fully parametric approach or a fully nonparametric approach. A semiparametric empirical likelihood method is proposed to construct confidence intervals for AUC by assuming a density ratio model for the diseased and non-diseased population densities. The limiting distribution of the semiparametric empirical log likelihood ratio statistic for AUC has a scaled chi-square distribution. The proposed semiparametric empirical likelihood approach is shown, via a simulation study, to be more robust than a fully parametric approach and is more accurate than a fully nonparametric approach. Some results on simulation and an analysis of two real examples are presented. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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