PhD, Statistics, University of Pittsburgh
Research interests include: group sequential methods; two-stage adaptive procedures (phase II / phase III); noninferiority / superiority / equivalence trials; statistics in basic science; statistical graphics; p value, confidence interval, unbiased estimate from a Simon's two-stage procedure
Honors and service include: Patrick G. Arbogast Collaborative Publication Awards (2014 and 2017); treasurer, American Statistical Association, Middle Tennessee Chapter (2022)
More information: biostat.app.vumc.org/TatsukiKoyama
Dr. Koyama's primary research interests revolve around flexible experimental designs for clinical trials and inference from the data that such flexible and adaptive designs produce, both in the Frequentist and Bayesian paradigms. He currently teaches the graduate-level course "Clinical trials and experimental design," and his collaborative research interests include comparative effectiveness research of treatments for localized prostate cancer and association between acute lung injury and air pollution, among others.