Richard Riley is a Reader in Biostatistics at the University of Birmingham, with a joint post in the School of Health and Population Sciences (Public Health, Epidemiology and Biostatistics) and the School of Mathematics.
He enthusiastically teaches a year-long Medical Statistics module to 3rd and 4th Year undergraduate maths students, and currently supervises three PhD students. He has received numerous healthcare related grants, from funders including the MRC and NIHR, and has published over 30 applied and methodological research articles. Particular research interests include meta-analysis, diagnostic test research, and prognosis research
Richard is a Statistics Editor for the British Medical Journal, an Associate Editor of Statistics in Medicine, and a co-convenor of the Cochrane Prognosis Methods Group.
Reader in Biostatistics
PhD in Medical Statistics, University of Leicester, 2005
MSc (with distinction) in Medical Statistics, University of Leicester, 1999
BSc (2(i)) in Mathematics with Statistics, University of Nottingham, 1998)
Richard Riley qualified with a BSc in Mathematics from the University of Nottingham (1998), and went on to complete an MSc with distinction (1999) and a PhD (2005) in Medical Statistics from the University of Leicester (2005). He worked as a Research Associate (1999 to 2001) in the Centre for Biostatistics at the University of Leicester, and as a Lecturer in the Centre for Medical Statistics and Health Evaluation at the University of Liverpool (2006-2008), where he also completed a Research Fellowship in Evidence Synthesis awarded by the Department of Health. He is now a Senior Lecturer in Medical Statistics at the University of Birmingham, with a joint post in the Department of Public Health, Epidemiology and Biostatistics and the School of Mathematics.
Richard specialises in the application and development of statistical methods for evidence synthesis and meta-analysis. His main methodological research interests include:
Statistical models for multivariate meta-analysis of multiple outcomes
Statistical methods for undertaking an individual participant data (IPD) meta-analysis
Approaches to combining IPD with aggregate data in meta-analysis
Investigating and dealing with publication and availability bias in IPD meta-analysis.
Particular clinical applications of interest (both in primary studies and systematic reviews) include:
Identifying and evaluating diagnostic tests
Identifying and evaluating prognostic factors and biomarkers
Developing, validating and assessing the impact of prognostic models and risk prediction models
Facilitating stratified medicine, in particular by identifying patient-level factors that interact with treatment effect (‘predictive markers’, ‘treatment-covariate interactions’)
A particular research passion is to improve the quality, design, conduct, analysis and reporting of prognosis research studies.
Richard has been a Statistics Editor of the British Medical Journal since 2009, an Associate Editor of Statistics in Medicine since 2011, and a co-convenor of the Cochrane Prognosis Methods Group since 2007. He enjoys teaching medical statistics to mathematics students, and often leads training courses on basic and advanced statistical issues, to either statistical or non-statistical professions. He also speaks regularly at national and international conferences.
Single Honours Mathematics (G100, G103, G141
Mathematics Majors: Mathematics with Business Management (G1N2); Mathematics with Engineering (J920); Mathematics with Philosphy (G1V5)
Joint Honours Mathematics: Mathematics & Computer Science (GG14); Pure Mathematics & Computer Science (GGC4); Mathematics & Sport Science (GC17); Mathematics & Music (GW13); Mathematics & Philosophy (GV15)
Theoretical Physics and Applied Mathematics (FG31)
Mathematics Minors: French Studies and Mathematics (GR11); German Studies and Mathematics (GR12)
Natural Sciences (CFG0, FCG0)
Ghada Abo-Zaid. Meta-analysis of prognostic factor studies using individual patient data
Ikhlaaq Ahmed. Development and validation of risk prediction models: from single studies to meta-analysis
Yemisi Takwoingi. Meta-analysis of diagnostic test accuracy studies.
Application of, and development of methods for, biostatistics; particularly in relation to:
- Meta-analysis and evidence synthesis, including individual patient data meta-analysis
- Diagnostic and prognostic test accuracy studies
- Prognostic factor studies
- Risk prediction and prognostic models
- Stratified medicine
Statistics Editor for the British Medical Journal
Associate Editor of Statistics in Medicine
Co-convenor of the Cochrane Prognosis Methods Group
In-press - Jackson D, Riley RD, White I. Multivariate meta-analysis: potential and promise. Stat Med
Riley RD, Higgins JP, Deeks JJ. The interpretation of random-effects meta-analysis. BMJ 2011; 342:d549 doi: 10.1136/bmj.d549
Riley RD, Steyerberg EW. Meta-analysis of a binary outcome using individual participant data and aggregate data. J Research Synthesis Methods 2010; 1: 2-9. DOI: 10.1002/jrsm.4
Hemmingway H, Riley RD, Altman DG. Ten steps toward improving prognosis research. BMJ 339: b4184. DOI: 10.1136/bmj.b4184
Riley RD, Lambert PC, Abo-Zaid G: Meta-analysis of individual participant data: conduct, rationale and reporting. BMJ 2010;340:c221. DOI 10.1136/bmj.c221.
Riley RD (2009). Multivariate meta-analysis: the effect of ignoring within-study correlation, J Roy Stat Soc: Series A. 172: 789-811. DOI: 10.1111/j.1467-985X.2008.00593.x
Riley RD, Sauerbrei W, Altman DG. Prognostic markers: the evolution of evidence from single studies to meta-analysis, and beyond. B J Cancer 2009; 100(8):1219-29. doi:10.1038/sj.bjc.6604999
Jones AP, Riley RD, Williamson PR, Whitehead A. Meta-analysis of longitudinal data. Clinical Trials. 2009;6(1):16-27. doi:10.1177/1740774508100984