Small area estimation of receiver operating characteristic curves for ordinal data under stochastic ordering-Reference-Cited by-同舟云学术

Small area estimation of receiver operating characteristic curves for ordinal data under stochastic ordering

Published:2020-05-15 Issue:10 Volume:39 Page:1514-1528
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statistics in Medicine

Author:

Jang Eun Jin¹^ORCID,Nandram Balgobin²,Ko Yousun³⁴,Kim Dal Ho⁵^ORCID

Affiliation:

1. Department of Information StatisticsAndong National University Andong South Korea

2. Department of Mathematical SciencesWorcester Polytechnic Institute Worcester Massachusetts

3. Program in Biomedical Radiation Sciences, Department of Transdisciplinary StudiesGraduate School of Convergence Science and Technology, Seoul National University Seoul South Korea

4. Biomedical Research Center, Asan Institute for Life SciencesAsan Medical Center Seoul South Korea

5. Department of StatisticsKyungpook National University Daegu South Korea

Funder

National Research Foundation of Korea

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.8493

Reference36 articles.

1. Receiver Operating Characteristic Analysis

2. ROC curve estimation: an overview;Gonçalves L;Revstat Stat J,2014

3. Maximum-likelihood estimation of parameters of signal-detection theory and determination of confidence intervals—Rating-method data

4. Form of empirical ROCs in discrimination and diagnostic tasks: Implications for theory and measurement of performance.

5. The Robustness of the "Binormal" Assumptions Used in Fitting ROC Curves

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Thermal power plants pollution assessment based on deep neural networks, remote sensing, and GIS: A real case study in Iran;Marine Pollution Bulletin;2023-07

2. Application of Characteristic Model-Based Principal Component Analysis in Optimization of Flowmeter Parameters;Mathematical Problems in Engineering;2021-08-19

3. The Predictive Model of Esophageal Squamous Cell Carcinoma Differentiation;Communications in Computer and Information Science;2021

4. Multi-task Classification Model Based On Multi-modal Glioma Data;2020 IEEE International Conference on Knowledge Graph (ICKG);2020-08

5. Survival Risk Prediction of Esophageal Cancer Based on Self-Organizing Maps Clustering and Support Vector Machine Ensembles;IEEE Access;2020