Department of Biostatistics Seminar/Workshop Series

On the equivalence of some medical cost estimators with censored data

Hongwei Zhao, Sc.D

Associate Professor, Department of Biostatistics and Computational Biology
University of Rochester, NY

Monday, May 5, 1:30-2:30pm, Light Hall, Room 202

Intended Audience: Persons interested in applied statistics, statistical theory, epidemiology, health services research, clinical trials methodology, statistical computing, statistical graphics, R users or potential users

With limited resources and sky-rocketing health care expenses, medical cost evaluation is being conducted more and more by health care organizations and policy makers. In clinical trials comparing different treatments, medical costs are frequently analyzed to evaluate the economical impacts of new treatment options. Since Lin et al.'s first finding in the problem of applying the survival analysis techniques to the cost data, many new methods have been proposed. In this talk, we establish analytic relationships among several widely adopted medical cost estimators that are seemingly different. Specifically, we report the equivalence among various estimators that were introduced by Lin et al., Bang and Tsiatis, and Zhao and Tian. Lin's estimators are formerly known to be asymptotically unbiased in some discrete censoring situations and biased otherwise, whereas all other estimators discussed here are consistent for the expected medical cost. Thus, we identify conditions under which these estimators become identical and, consequently, the biased estimators achieve consistency. We illustrate these relationships using an example from a clinical trial examining the effectiveness of implantable cardiac defibrillators in preventing death among people who had prior myocardial infarctions.
Topic revision: r1 - 30 Apr 2008, DianeKolb

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