/content/dam/www/people-profile-photos/w/ching-yun-wang/ching-yun-wang-d.jpg
Wang
Ching-Yun Wang, PhD
- Professor, Biostatistics Program, Public Health Sciences Division, Fred Hutch
- Member, Translational Data Science Integrated Research Center (TDS IRC), Fred Hutch
- Affiliate Professor, Biostatistics, University of Washington
Background
Dr. Ching-Yun Wang is a biostatistician whose research interests center on measurement error, missing data, joint modeling of survival and longitudinal data, and analysis of clinical trials. His research group has been involved with many biomedical and epidemiological studies, such as trials testing how diet and physical activity can prevent cancer. For example, one such study in overweight and obese women found that weight loss reduced the levels of hormones related to breast cancer risk. He has also worked on trials of screening strategies for colorectal cancer. His expertise also includes the development of semiparametric regression models, and high-dimensional biomarker data and classification.
Education
PhD, Statistics, Texas A&M University-College Station, 1993
MS, Applied Mathematics, National Tsing-Hua University, 1985
Research Interests
Missing Data, Measurement Error and Nutritional Epidemiology
Honors and Awards
2002 - The H.O. Hartley Award, Department of Statistics, Texas A&M University
Current Projects
Project Title: Exercise-Stimulated Signaling Pathways Associated with Cancer Development and Progression (BCRF-23-107)
Principal Investigator: Anne McTiernan
Role on project: Co-Investigator
The goal of this study is to test the effects of acute exercise on biomarkers of breast cancer risk and prognosis.
Project Title: An AHEI Dietary Intervention to Reduce Pain in Women with Endometriosis (R01NR017951)
Principal Investigator: Holly Ruth Harris
Role on project: Co-Investigator
This randomized controlled trial tests a 12-week diet based on the Alternative Healthy Eating Index-2010 to assess its impact on pain, quality of life, and inflammation in women with laparoscopically confirmed endometriosis. Findings will help identify modifiable dietary factors to reduce pain and enhance well-being.
Project Title: Statistical methods for analyzing objectively measured physical activity data (R01HL130483)
Principal Investigator: Chongzhi Di
Role on project: Co-Investigator
This project aims to develop new analytic tools for understanding how accumulation patterns of physical activity, sedentary behavior and sleep in the 24-hour activity cycle are associated with health outcomes, such as cardiovascular diseases.
Project Title: Breast Cancer Diagnostic Kit to Improve Early Diagnosis in Uganda (U01CA292550)
Principal Investigator: John R. Scheel
Role on project: Co-Investigator
Delayed breast cancer diagnosis in low-resource settings leads to poorer outcomes. A portable diagnostic kit combining ultrasound and molecular tools is being tested in the U.S. and Uganda to improve early detection and guide treatment.
Project Title: Statistical Methods for Analysis of Tumor Heterogeneity in Genetic Epidemiology (R01CA189532)
Principal Investigator: Li Hsu
Role on project: Co-Investigator
This project develops statistical methods for assessing association of tumor heterogeneity with clinical outcomes
Selected Scientific Publications
Song X, Wang CY. Proportional Hazards Model with Covariate Measurement Error and Instrumental Variables. J Am Stat Assoc. 2014 Dec 1;109(504):1636-1646. doi: 10.1080/01621459.2014.896805. PMID: 25663724; PMCID: PMC4315262.
Wang CY, Cullings H, Song X, Kopecky KJ. Joint nonparametric correction estimator for excess relative risk regression in survival analysis with exposure measurement error. J R Stat Soc Series B Stat Methodol. 2017 Nov;79(5):1583-1599. doi: 10.1111/rssb.12230. Epub 2017 Feb 27. PMID: 29354018; PMCID: PMC5773020.
Yu H, Cheng YJ, Wang CY. Methods for multivariate recurrent event data with measurement error and informative censoring. Biometrics. 2018 Sep;74(3):966-976. doi: 10.1111/biom.12857. Epub 2018 Feb 13. PMID: 29441520; PMCID: PMC6089684.
Wang CY, Song X. Semiparametric regression calibration for general hazard models in survival analysis with covariate measurement error; surprising performance under linear hazard. Biometrics. 2021 Jun;77(2):561-572. doi: 10.1111/biom.13318. Epub 2020 Jun 25. PMID: 32557567; PMCID: PMC7746575.
Wang CY, Hsu L, Harrison T. Robust best linear weighted estimator with missing covariates in survival analysis. Stat Med. 2024 Apr 30;43(9):1790-1803. doi: 10.1002/sim.10044. Epub 2024 Feb 25. PMID: 38402690; PMCID: PMC11093525.