Guofen Yan, Ph.D.

Guofen YanDr. Yan is a biostatistician with expertise in survival, longitudinal, and hierarchical models, and analysis of population registry databases (such as Medicare claims, U.S. Renal Data System). Her independent researches, funded by NIH/NIDDK R01 grant (PI) and AHRQ R01 grant (site PI), focus on survival and recurrent events, competing risks, longitudinal associations, determinants of racial and ethnic disparities in outcomes and care for chronic kidney disease, and multilevel longitudinal associations of contextual factors, processes of care and outcomes in US health care units. Dr. Yan has collaborated with many clinical investigators in various diseases and clinical specialties with contributions ranging from study design, statistical analysis to grant applications and manuscripts. She has also been a primary statistician for multiple NIH-funded large-scale multicenter clinical trials.

Associate Professor of Biostatistics
Ph.D., Statistics, 2003, Case Western Reserve University

P.O. Box 800717
Tel: 1-434-982-6422
Fax: 1-434-243-5787
Old Med School Room 3881


  • Design and analysis of large-scale, multi-center, phase II and III clinical trials
  • Survival analysis, longitudinal data analysis, multilevel models, competing risks analysis
  • Development and validation of risk predictive models
  • Clinical epidemiology and outcome research, using disease registries, electronic medical records, and Medicare claims data

Research Interests

  • Bayesian methodology and predictive inference
  • Models for survival, longitudinal, and clustered (multilevel) data
  • Epidemiology, outcomes, and racial/ethnic disparities in CKD/ESRD

Teaching Responsibilities

STAT 5559/PHS 7440/PHS 5440: Bayesian Analysis

National Service

  • Voting member (2013-present), the Medicare Evidence Development & Coverage Advisory Committee (MEDCAC), Centers for Medicare & Medicaid Services (CMS) of U.S. Department of Health and Human Services
  • Member (2014-present), the CMS Technical Expert Panel (TEP) for Yale New Haven Health Services Corporation Center for Outcomes Research and Evaluation (CORE) at Yale University
  • Proposal Reviewer (2014), National Science Foundation (NSF) Methodology, Measurement, and Statistics (MMS) Program
  • Member (2013), NIH/NIDDK Special Emphasis Review Panel for United States Renal Data System (USRDS) Special Study Centers (U01)

Other Information

Before joining UVA in 2005, Dr. Yan had worked in the Department of Biostatistics and Epidemiology at the Cleveland Clinic Foundation (CCF) for many years. There she collaborated closely with nephrologists and served as a primary statistician for several NIH-funded large-scale multi-center clinical trials for which CCF served as the Data Coordinating Center, including the landmark Hemodialysis Study (HEMO). At UVA, she has collaborated with clinicians and researchers in School of Medicine and School of Nursing on a number of NIH U-level grants, clinical trials, and investigator-initiated R01 grants. She has also served as a statistics mentor for physicians and health-service researchers on their NIH K awards, and for more than two dozen doctoral students on their dissertations. Dr. Yan’s own research has been funded by NIH/NIDDK. She is the PI for a NIH/NIDDK R01 grant on racial disparity in end-stage renal disease with the investigators from multiple institutions.

Selected Recent Publications

  • Yan G, Cheung AK, Greene T, Yu AJ, et al. (2015). Interstate variation in receipt of nephrologist care in US patients approaching ESRD: race, age, and state characteristics. Clinical Journal of the American Society of Nephrology 10(11): 1979-88.
  • Yan G, Norris KC, Greene T, Yu AJ, et al. (2014). Race/ethnicity, age, and risk of hospital admission and length of stay during the first year of maintenance hemodialysis. Clinical Journal of the American Society of Nephrology 9(8): 1402-9.
  • Yan G, Norris KC, Xin W, Ma JZ, et al. (2013). Facility size, race and ethnicity, and mortality for in-center hemodialysis. Journal of the American Society of Nephrology 24(12): 2062-70.
  • Yan G, Norris KC, Yu AJ, Ma JZ, et al. (2013). The Relationship of Age, Race, and Ethnicity with Survival in Dialysis Patients. Clinical Journal of the American Society of Nephrology8(6): 953-61.
  • Yan G, Cheung AK, Ma JZ, Yu AJ, et al. (2013). The Associations between Race and Geographic Area and Quality-of-Care Indicators in Patients Approaching ESRD. Clinical Journal of the American Society of Nephrology 8 (4): 610-618.
  • Yan G and Sedransk J. (2011). Improved inference for a linear mixed-effects model when the subpopulation effects are clustered. Journal of Statistical Planning and Inference 141: 3489–3497.
  • Yan G and Greene T. (2011). Statistical analysis and design for estimating accuracy in clinical-center classification of cause-specific clinical events in clinical trials. Clinical Trials 8(5): 571 – 580.
  • Johnston KC and Yan G. (2011). Acute Physiology of Stroke Score. Stroke 42(8):2336-2338.
  • Yan G and Sedransk J. (2010). The effect of sample composition on inference for random effects using Normal and Dirichlet process models. Journal of Data Science 8(4): 589-605.
  • Yan G and Greene T. (2008). Investigating the effects of ties on measures of concordance. Statistics in Medicine 27(21):4190-4206.
  • Yan G and Sedransk J. (2010). A Note on Bayesian Residuals in Hierarchical Model Diagnostic. Statistical Papers 51:1–10.
  • Yan G and Sedransk J. (2007). Bayesian Diagnostic Techniques for Detecting Hierarchical Structure. Bayesian Analysis 2, 735-760.
  • Yan G and Sedransk J. (2006). Exploring the use of subpopulation membership in Bayesian hierarchical model assessment. Journal of Data Science 4: 413-424.
  • Cheung A, Rocco M, Yan G, Leypoldt J, et al. (2006). Serum ß2-microglobulin levels predict mortality in dialysis patients: Results of HEMO Study. Journal of the American Society of Nephrology 17:546-555.
  • Unruh M, Yan G , Radeva M, Hays Rd, et al. (2003). Bias in assessment of health-related quality of life in a hemodialysis population: a comparison of self-administered and interviewer-administered surveys in the HEMO Study. Journal of the American Society of Nephrology 14: 2132-2141.
  • Ng YH, Meyer KB, Kuse JW, Yan G, et al. (2006). Hemodialysis timing, survival, and cardiovascular outcomes in the Hemodialysis (HEMO) Study. American Journal of Kidney Disease 47(4):614-24.
  • Unruh M, Miskulin D, Yan G, Hays RD, et al (2004). Racial differences in health-related quality of life among hemodialysis patients. Kidney International, 65:1482-1491.
  • Unruh M, Benz R, Greene T, Yan G, et al. (2004). Effects of hemodialysis dose and membrane flux on health-related quality of life in the HEMO Study. Kidney International 66:1-12.
  • Cheung AK, Sarnak M, Yan G, Berkoben M, et al. (2004). Cardiac diseases in maintenance hemodialysis patients: Results of the HEMO study. Kidney International 65: 2380-2389.
  • Allen KL, Miskulin D, Yan G, Dwyer JT, et al. (2002). Association of nutritional markers with physical and mental health status in prevalent hemodialysis patients from the HEMO study. Journal of Renal Nutrition 12(3):160-9.
  • Cheung AK, Yan G, Greene T, Daugirdas JT, et al. (2002). Seasonal variations in clinical and laboratory variables among chronic hemodialysis patients. Journal of the American Society of Nephrology 13(9):2345-52.
  • Rocco MV, Yan G, Gassman J, Lewis JB, et al. (2002). Comparison of causes of death using HEMO Study and HCFA end-stage renal disease death notification classification systems. The National Institutes of Health-funded Hemodialysis. Health Care Financing Administration. American Journal of Kidney Disease 39(1):146-53.