Rebecca Whittle
Senior Researcher in Medical Statistics
My main research interests lie in prognosis and prediction, with a focus on improving the reporting and development of prediction research. I joined the Centre for Statistics in Medicine in January 2023 working on statistical methodology research funded by Cancer Research UK (CRUK), and various applied medical research projects for the National Institute for Health and Care Research (NIHR) Blood and Transplant Research Unit (BTRU) in Data Driven Transfusion Practice.
Prior to this, much of my work experience has been as a medical statistician at Keele University, concurrently working on prognosis related studies (both applied and methodology) whilst providing statistical support for various other clinical projects in the School of Medicine, with a particular focus on the use of large data from electronic health records (EHR).
I completed a PhD in Medical Statistics at Keele University in 2022, which involved a mixture of applied and methodology work covering the areas of prognosis, prediction, individual participant data (IPD) meta-analysis and measurement error. Before this I completed a BSc in Mathematics at the University of Leeds (2012) and an MSc in Medical Statistics at the University of Leicester (2013).
Recent publications
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The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols
Journal article
Dhiman P. et al, (2023), Nature machine intelligence, 5, 816 - 817
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Calculating the power of a planned individual participant data meta-analysis of randomised trials to examine a treatment-covariate interaction with a time-to-event outcome.
Journal article
Riley RD. et al, (2023), Res synth methods
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Trends in gabapentinoid prescribing in UK primary care using the Clinical Practice Research Datalink: an observational study
Journal article
Ashworth J. et al, (2023), The lancet regional health - europe, 27, 100579 - 100579
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Rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis epidemiology in England from 2004 to 2020: An observational study using primary care electronic health record data.
Journal article
Scott IC. et al, (2022), Lancet reg health eur, 23
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Calculating the power to examine treatment-covariate interactions when planning an individual participant data meta-analysis of randomized trials with a binary outcome.
Journal article
Riley RD. et al, (2022), Stat med, 41, 4822 - 4837