Hypothesis testing methods for multi-reader multi-case studies-Reference-Cited by-同舟云学术

Hypothesis testing methods for multi-reader multi-case studies

Published:2022-08-09 Issue: Volume: Page:1-14
ISSN:2470-9360
Container-title:Biostatistics & Epidemiology
language:en
Short-container-title:Biostatistics & Epidemiology

Author:

Zhang Huan¹,Li Yuying²,Lin Qiushi³,Zhou Xiao-Hua²³,Feng Guoshuang⁴⁵

Affiliation:

1. Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China

2. Department of Biostatistics, School of Public Health, Peking University, Beijing, People's Republic of China

3. Beijing International Center for Mathematical Research, Peking University, Beijing, People's Republic of China

4. Big Data and Engineering Research Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, People's Republic of China

5. Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing, People's Republic of China

Funder

Natural Science Foundation of China

Beihang University & Capital Medical University Advanced Innovation Center

Publisher

Informa UK Limited

Subject

Health Informatics,Epidemiology

Link

https://www.tandfonline.com/doi/pdf/10.1080/24709360.2022.2075603

Reference18 articles.

1. Hypothesis testing of diagnostic accuracy for multiple readers and multiple tests an anova approach with dependent observations

2. Receiver Operating Characteristic Rating Analysis

3. Hillis SL. A comparison of denominator degrees of freedom methods for multiple observer ROC analysis. 2007.

4. A marginal model approach for analysis of multi-reader multi-test receiver operating characteristic (ROC) data

5. Analysis of unbalanced mixed model data: A case study comparison of ANOVA versus REML/GLS