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, MRBIII Conference Room 1220
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.