Medical Statistics Group
Quantitative thinking is fundamental to most medical research, and the Medical Statistics Group collaborates with all areas of the School of Health and Related Research, and with the other schools in the Faculty of Medicine, and with the wider medical research community.
The Medical Statistics Group (MSG) aims to:
- Develop and maintain a strong portfolio of research in statistical areas relevant to medical and health-related research.
- Collaborate with colleagues to develop and deliver high-quality research, that is recognised both nationally and internationally.
- Develop and deliver excellent quality research-informed teaching relevant to today's students, at undergraduate, postgraduate and professional development levels.
- To contribute to the corporate aims of the School of Health and Related Research (ScHARR), Faculty and the University and engage with the wider external community in a manner that will benefit the group, ScHARR and the University.
The Group operates in the three main areas of research, teaching and consultancy.
The Medical Statistics Group undertakes a broadly based research programme in applied projects and in statistical methodology. The applied work generates methodological questions, and the methodological research feeds back into the applied studies.
The Medical Statistics Group works on the application of statistical methododology to substantive issues in health research. This frequently requires the development of existing and new methodology.
We have strong links with the NHS, providing a research design service (RDS) through the NIHR RDS for Yorkshire and Humber, and collaborating with health researchers across South Yorkshire and beyond. We also work with industrial, national and international partners in the health area.
Some examples of our methodological interests are:
- Clinical trial design and analysis, particularly sample size
- Cluster Randomised trials
- Design, Analysis and interpretation of studies with Health Related Quality of Life (HRQoL) outcome measures.
- Computer intensive methods – the bootstrap.
- Health Services Research and Technology Assessment.
- Economic Evaluations alongside clinical trials.
- Study design and sample size determination.
- Time series analysis.
- Clinical pharmacology.
- Bias in trials.
Current and completed research projects
NIHR Research Methods Fellowship. Developing performance indicators for Emergency Departments. Nicholl J and Jacques RM. £97,000. 2017.
NIHR Research Methods Fellowship. Assessing feasibility in publicly funded trials. Goodacre S and Julious SJ. £95,000. 2016.
Lewis J, Stone T, Simpson R, Jacques R, O’Keeffe C, Croft S & Mason S (2021) Patient compliance with NHS 111 advice: Analysis of adult call and ED attendance data 2013–2017. PLoS ONE, 16(5).
Dimairo M, Pallmann P, Wason J, Todd S, Jaki T, Julious SA, Mander AP, Weir CJ, Koenig F, Walton MK , Nicholl JP et al (2020) The Adaptive designs CONSORT Extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design. BMJ, 369.
Bradburn MJ, Lee EC, White DA, Hind D, Waugh NR, Cooke DD, Hopkins D, Mansell P & Heller SR (2020) Treatment effects may remain the same even when trial participants differed from the target population. Journal of Clinical Epidemiology 124: 126-138.
Edwards JM, Walters SJ, Kunz C & Julious SA (2020) A systematic review of the “promising zone” design. Trials, 21.
The Medical Statistics Group aims to develop and deliver excellent quality research-informed teaching relevant to today's students, at undergraduate, postgraduate and professional development levels.
The statisticians' in the Medical Statistics Group teach and examine across the whole range of ScHARR's teaching activities.
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