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Sofia Massa


OCTRU Lead Statistician

Sofia joined NDORMS in February 2023 and she is interested in developing sound and rigorous statistical models for estimating parameters of interest from clinical trials data and health research data.

Before joining NDORMS she was a Senior Statistician and Module Lead in Statistics in NDPH where she co-lead projects on large population studies (UKB, CKB, Cuba Prospective Study, Life Line Screening, TILDA among others) on developing risk prediction models for cardiovascular disease. She also investigated the association of infectious respiratory diseases with smoking and adiposity and was involved in further research in frailty and its assessment in the older population. During this period she was also a Statistical Editor for Cochrane Reviews.

During her PhD she worked on theoretical aspects of Statistics introducing the concept of structural meta-analysis as the combination of evidence from studies where the interest is in finding shared conditional independence relations across statistical models with partially overlapping variables.She found conditions under which conflicting evidence can be encoded allowing for different types of statistical combinations of models building on the concept of hyper Markov laws. The estimation of the parameters of the models expanded the use of the EM algorithm for missing data.

She also extended the use of Gaussian graphical models for case-control studies from microarray data where the interest is in testing the equality of means across two or more experimental conditions. The equality of means was augmented with a further test about the equality of the concentration matrices representing the conditional independence relations.

Sofia has also been a Departmental Lecturer in Statistics teaching Statistical Theory and applications at all levels (college tutorials, undergraduate and MSc students and first year DPhil students) and continuining her research in graphical models and their applications.

She is currently supervising four DPhil students and has supervised one DPhil student to completion. She has supervised MSc students across Statistics, Applied Statistics and Population Health. She has also been an assessor for MSc dissertations and exams and internal and external examiner for DPhil Theses.

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