Xiao-Hua Andrew Zhou's Home Page

Xiao-Hua (Andrew) Zhou,Ph.D
Professor, Department of Biostatistics
School of Public Health
Adjunct Professor, Department of Psychiatry and Behavioral Science
School of Medicine
University of Washington
Director and Research Career Scientist, Biostatistics Unit
U.S. Department of Veterans Affairs Seattle Medical Center

email: azhou@u.washington.edu
office: Met Park West #1400, Puget Care System Care and H-655E, HSB, University of Washington
phone: 206 - 277- 3588

Academic History

I received a B.Sc. in Mathematics from Sichuan University in 1984, a M.Sc. in Statistics from the University of Calgary in 1987, and a Ph.D in Biostatistics from Ohio State University in 1991. I finished a two-year post-doc fellowship in Biostatistics at Harvard University in 1993. I joined the Division of Biostatistics in Indiana University School of Medicine as Assistant Professor in 1993 and was promoted to Associate Professor in 1997. In 2002, I accepted a position as the Director of Biostatistics Unit at the U.S. Department of Veterans Affairs Puget Sound Health Care System . In 2003, I was promoted to Full Research Professor in the Department of Biostatistics at University of Washington . I became a Full Professor at the University of Washington in 2005.

Academic Accomplishments and Honors

I was elected to be a member of the International Statistical Institute in 1998, and in 2004 I was elected to be a Fellow of the American Statistical Association. I served as Chair of the Section on Statistics in Epidemiology of the American Statistical Association in 2004 and Chair of the Health Policy Statistics Section of the American Statistical Association in 2011. I am currently serving as Chair of the Mental Health Statistics Section of the American Statistical Association and as President of VA Statisticians' Association (VASA) VA Statisticians' Association (VASA) . I served as a member of the Study Section of National Institute of Health and am currently serving my second four-year term on the Radiological Devices Advisory Committee in Center for Devices and Radiological Health in U.S. Food and Drug Administration (FDA) . I am also a consultant for the Oncologic Drugs Advisory Committee at the Center for Drug Evaluation and Research, U.S. Food and Drug Administration(FDA). I received a Research Career Scientist Award (RCS) from the U.S. Federal Government Department of Veterans Affairs in 2007. In collaboration with two of my colleagues, I have written the first textbook on statistical methods in diagnostic medicine. The first edition was published by Wiley & Sons in 2002 and the second edition was published in 2011. See Statistical Methods in Diagnostic Medicine for detailed information.

Research Areas:

My areas of research have primarily focused on the development of new statistical methods for health services research studies, for clinical trials with non-compliance, and for studies on the accuracy of diagnostic tests. In addition, I has been collaborating with other clinical researchers on research pertaining to health services, Autism Spectrum Disorders (ASD), and Alzheimer's Disease (AD) since 1993.

I have published a total of 198 peer-reviewed, SCI papers. Within my own area of statistical research, I have 143 papers in refereed journals. In terms of collaborative research, I am a co-author for 55 publications in the field of medical sciences.

Statistical methods in diagnostic medicine:
Since 1993, I have been working on the development of new statistical methods for studies related to diagnostic tests. My efforts in this area have been supported by a R29 grant (FIRST award) from the National Institute of Health (NIH), a R01 grant from the National Institute of Health, and a research grant from the National Science Foundation. I have published more than 40 statistical papers in this area. In 2002, along with two co-authors, I published the first comprehensive statistical textbook in diagnostic medicine, which was published by Wiley & Sons and can be ordered at Amazon.com . The second edition of this book was published by Wiley in 2011.
The analysis of skewed cost data:
Another of my areas of major statistical research is the development of new methods for health services research, particularly for studies on health care costs and the factors affecting such costs. Since 1995, I have been working on the development of new statistical methods for the analysis of health care costs that can adjust for special characteristics of health care costs. My work has been supported by a R03 grant from the Agency for Health Care Policy and Research (AHCPR), two R01 grants from National Institute of Health (NIH), and a research grant from the U.S. Federal Government Department of Veterans Affairs. I have published more than 30 statistical papers in this area.
Causal inferences in observational studies:
My third area of active research pertains pertains to the development of new statistical methods for an observational study, which is an important tool for obtaining accurate information about the effects of drugs or treatments in the usual practice of patient care. A major problem with the causal inferences in an observational study is confounding by indication, which means that the background characteristics of drug treatments often differ. In collaboration with my colleagues, I published a paper on the propensity-score methodology and another paper on a bootstrap confidence interval for the treatment effect using the propensity-score methodology.
Causal inferences in randomized with non-compliance:
My fourth area of active research is on the development of new statistical methods for the analysis of encouragement design studies (EDS). In a randomized EDS, clinicians are randomly assigned to receive or not to receive an encouragement for the use of the treatment on their patients. Rigorous evaluation on the causal effects of the treatment on patient outcomes in a randomized EDS is often difficult because of the issue of clinician compliance with the intervention in a randomized EDS. The clinicians can decide to comply or not to comply with the encouragement or to perform the suggested treatment regardless of whether they have been encouraged to do so. Ignoring the issues of clinician non-compliance in these studies can lead to unreliable inferences and predictions. I have published more than 10 papers in this area. My efforts in this area are currently being supported by a R01 grant from the National Institute of Health (NIH).
Personalized Medicine Using Genomic Information: My fifth area of research is on the development of new statistical methods for assessing prognostic and predictive values of biomarkers. A prognostic biomarker indicates the likelihood of outcomes independent of treatments. A predictive biomarker predicts the clinical benefits from a specific therapy based on the biomarker status. The rapid advancement of molecular genetic technology and the boom of molecular diagnostics companies have set the stage for a new era in personalized treatments. Patient response to treatments are often heterogeneous. By identifying patients using biomarkers who are more or less likely to benefit from a treatment, we are able to provide the most effective treatment to those who are most in need. This research has been supported by a research grant from the U.S. Federal Government Department of Veterans Affairs.

Collaborative Research Interests:

Since 1993, I have been engaged in medical and health services research in collaboration with other researchers. These studies have resulted in more than 50 publications in refereed medical journals.

Health Services Research: health services research is a "multidisciplinary field that examines the use, costs, quality, accessibility, delivery, organization, financing, and outcomes of health services to increase knowledge and understanding of the structure, process, and effects of health services for individuals and populations"
National Alzheimer's Coordinating Center (NACC): The NACC facilitates collaborative research among the approximately 30 Alzheimer's Disease Centers funded by the National Institute on Aging and maintains a Uniform Data Set (UDS) database of information collected by the Alzheimer's Disease Centers regarding patients with Alzheimer's Disease and controls.
Profiling Quality of Hospitals
Assisted Living Research.
Mental Health.