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Chiara Di Gravio is first author of Biometrics paper

Posted by on Thursday, March 7, 2024 in News.

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).

Graphs showing Efficiency of two-phase ODS designs and analysis procedures relative to SRS with the ML for βx, βxt, and βx + 5βxt.
Figure 1 in “Efficient designs and analysis of two-phase studies with longitudinal binary data.” Copyright Chiara Di Gravio, Jonathan Schildcrout, and Ran Tao 2024. Published by Oxford University Press on behalf of The International Biometric Society.