Applied Statistics - Alan Zaslavsky 

 This week the Applied Statistics Workshop will present a talk by Alan Zaslavsky, Professor of Health Care Policy (Statistics) in the Department of Health Care Policy at Harvard Medical School.   Dr. Zaslavsky's statistical research interests include surveys, census methodology, small area estimation, official statistics, missing data, hierarchical modeling, and Bayesian methodology.  His research topics in health care policy center on measurement of the quality of care provided by health plans through consumer assessments and clinical and administrative data.   Among his current major projects are (1) the Consumer Assessments of Healthcare Providers and Systems (CAHPS) survey implementation for the Medicare system, (2) methodology for surveys in psychiatric epidemiology, centered on validation of the CIDI-A (adolescent) survey in the National Comorbidity Study-Adolescent, and (3) studies on determinants of quality of care for cancer, including both the Statistical Coordinating Center and a research site for the NCI-funded CanCORS (Cancer Consortium for Outcomes Research and Surveillance) study.  Other research interests include measurement of disparities in health care, and privacy and confidentiality for health care data.  

 He is a member of the Committee on National Statistics (CNSTAT) of the National Academy of Sciences and has served on CNSTAT panels on census methodology, small area estimation and race/ethnicity measurement, as well as the Committee on the National Quality Report on Health Care Delivery of the Institute of Medicine. 

 Dr. Zaslavsky received his A.B. degree at Harvard College, his M.S. at Northeastern University, and his Ph.D. at the Massachusetts Institute of Technology.  He is a Fellow of the American Statistical Association. 

 Professor Zaslavsky will present a talk entitled " Modeling the covariance structure of random coefficients to characterize the quality variation in health plans ." The presentation will be at noon on Wednesday, November 29th, in Room N354, CGIS North, 1737 Cambridge St. Lunch will be provided.