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Full-Text Articles in Biostatistics

A Modular Framework For Early-Phase Seamless Oncology Trials, Philip S. Boonstra, Thomas M. Braun, Elizabeth C. Chase Jan 2020

A Modular Framework For Early-Phase Seamless Oncology Trials, Philip S. Boonstra, Thomas M. Braun, Elizabeth C. Chase

The University of Michigan Department of Biostatistics Working Paper Series

Background: As our understanding of the etiology and mechanisms of cancer becomes more sophisticated and the number of therapeutic options increases, phase I oncology trials today have multiple primary objectives. Many such designs are now 'seamless', meaning that the trial estimates both the maximum tolerated dose and the efficacy at this dose level. Sponsors often proceed with further study only with this additional efficacy evidence. However, with this increasing complexity in trial design, it becomes challenging to articulate fundamental operating characteristics of these trials, such as (i) what is the probability that the design will identify an acceptable, i.e. safe …


Strengthening Instrumental Variables Through Weighting, Douglas Lehmann, Yun Li, Rajiv Saran, Yi Li Mar 2016

Strengthening Instrumental Variables Through Weighting, Douglas Lehmann, Yun Li, Rajiv Saran, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

Instrumental variable (IV) methods are widely used to deal with the issue of unmeasured confounding and are becoming popular in health and medical research. IV models are able to obtain consistent estimates in the presence of unmeasured confounding, but rely on assumptions that are hard to verify and often criticized. An instrument is a variable that influences or encourages individuals toward a particular treatment without directly affecting the outcome. Estimates obtained using instruments with a weak influence over the treatment are known to have larger small-sample bias and to be less robust to the critical IV assumption that the instrument …