Congratulations to recent PhD graduate Chiara Di Gravio and her dissertation advisers, professor Jonathan Schildcrout and associate professor Ran Tao, on the publication of Efficient designs and analysis of two-phase studies with longitudinal binary data in the March 2024 issue of Biometrics. The paper presents a flexible full-cohort analysis method known as an efficient sieve maximum likelihood estimator (SMLE). The work was made possible in part by ACCRE, Vanderbilt's high-performance computing cluster, with data from the Lung Health Study.
Dr. Di Gravio graduated from Vanderbilt in August 2023 and is now a postdoc at Imperial College London. In December 2023, she delivered a talk titled "The relationship between self-reported persistent symptoms post-COVID-19 and employment among adults in England, UK" at the Demystifying Long COVID International Conference in Madrid. The presentation was live-tweeted in English by Jon-Ruben van Rhijn and in French by ApresJ20 (Association Covid Long France).