DESCRIPTION (Adapted from applicant's abstract): The main theme of this
project is the investigation of methodology for the censored or missing data
that commonly arises in clinical trials and cohort studies in cancer
research. More specifically, we will investigate: 1. Methods for
analyzing the cost or resource utilization in cancer studies with incomplete
follow-up. 2. Adaptive inference based on families of either regression
models or rank tests when a most efficient model cannot be specified in
advance. 3. Models that adjust for missing data or partial information in
either the cause of failure in right censored data or in longitudinally
measured response data, such as in quality of life scores. 4. Group
sequential designs for monitoring survival probabilities, as opposed to
hazard ratios, in cancer clinical trials.
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