Literature DB >> 18613272

Semi-parametric maximum likelihood estimates for ROC curves of continuous-scale tests.

Xiao-Hua Zhou1, Huazhen Lin.   

Abstract

In this paper, we propose a new semi-parametric maximum likelihood (ML) estimate of a receiver operating characteristic (ROC) curve that satisfies the property of invariance of the ROC curve and is easy to compute. We show that our new estimator is sqrt[n]-consistent and has an asymptotically normal distribution. Our extensive simulation studies show that the proposed method is efficient and robust. Finally, we illustrate the application of the proposed estimator in a real data set. Copyright 2008 John Wiley & Sons, Ltd.

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Year:  2008        PMID: 18613272      PMCID: PMC2662369          DOI: 10.1002/sim.3349

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  6 in total

1.  Distribution-free ROC analysis using binary regression techniques.

Authors:  Todd A Alonzo; Margaret Sullivan Pepe
Journal:  Biostatistics       Date:  2002-09       Impact factor: 5.899

2.  The analysis of placement values for evaluating discriminatory measures.

Authors:  Margaret Sullivan Pepe; Tianxi Cai
Journal:  Biometrics       Date:  2004-06       Impact factor: 2.571

3.  Semi-parametric estimation of the binormal ROC curve for a continuous diagnostic test.

Authors:  Tianxi Cai; Chaya S Moskowitz
Journal:  Biostatistics       Date:  2004-10       Impact factor: 5.899

4.  Maximum likelihood estimation of receiver operating characteristic (ROC) curves from continuously-distributed data.

Authors:  C E Metz; B A Herman; J H Shen
Journal:  Stat Med       Date:  1998-05-15       Impact factor: 2.373

5.  Statistical comparison of two ROC-curve estimates obtained from partially-paired datasets.

Authors:  C E Metz; B A Herman; C A Roe
Journal:  Med Decis Making       Date:  1998 Jan-Mar       Impact factor: 2.583

6.  The robustness of the "binormal" assumptions used in fitting ROC curves.

Authors:  J A Hanley
Journal:  Med Decis Making       Date:  1988 Jul-Sep       Impact factor: 2.583

  6 in total
  1 in total

1.  Superiority of combining two independent trials in interim futility analysis.

Authors:  Qiqi Deng; Ying-Ying Zhang; Dooti Roy; Ming-Hui Chen
Journal:  Stat Methods Med Res       Date:  2019-04-08       Impact factor: 3.021

  1 in total

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