Dr Richard David Riley BSc, MSc, PhD

Senior Lecturer in Medical Statistics

School of Mathematics

Dr Richard David Riley

Contact details

Telephone +44 (0) 121 414 7508

Fax +44 (0) 121 414 3389

Email r.d.riley@bham.ac.uk

School of Mathematics
Watson Building
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

About

Richard Riley is a Senior Lecturer in Medical Statistics at the University of Birmingham, with a joint post in the School of Mathematics and the Department of Public Health, Epidemiology and Biostatistics (School of Health and Population Sciences).

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.

Qualifications

Senior Lecturer in Medical Statistics:

  • 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)

Biography

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.

Teaching

  • 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)

Postgraduate supervision

  • 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

Research

Application of, and development of methods for, biostatistics; particularly in relation to:

  • Meta-analysis and evidence synthesis
  • Diagnostic and prognostic test accuracy studies
  • Prognostic factor studies
  • Risk prediction and prognostic models
  • Biomarkers
  • Stratified medicine

Other activities

  • Statistics Editor for the British Medical Journal
  • Associate Editor of Statistics in Medicine
  • Co-convenor of the Cochrane Prognosis Methods Group

Publications

Selected recent publications:

Journal Articles

Submitted

  • Hubner R, Riley RD, Billingham C, Popat S. Systematic review and meta-analysis of the predictive ability of ERCC-1 in non-small cell lung carcinoma. J Clin Oncol
  • Abo Zaid, Riley RD, Sauerbrei W. Individual patient data meta-analysis of prognostic factor studies: state of the art? Int J Epi
  • Crowther M, Riley RD, Wang J, Staessen J, Gueyffier F, Lambert PC. Individual participant data meta-analysis of survival data using Poisson regression models. Stat Med

In-press 

  • Jackson D, Riley RD, White I. Multivariate meta-analysis: potential and promise. Stat Med

2011

  • Riley RD, Higgins JP, Deeks JJ. The interpretation of random-effects meta-analysis. BMJ 2011; 342:d549 doi: 10.1136/bmj.d549

2010 

  • S Tandon, C Tudur-Smith, RD Riley, MT Boyd, TM Jones. 2010. A Systematic Review of p53 as a Prognostic Factor of Survival in Squamous Cell Carcinoma of the Four Main Anatomical Subsites of the Head and Neck, Cancer Epidemiology Biomarkers & Prevention, 19, 2, 574-587. DOI: 10.1158/1055-9965.EPI-09-0981
  • Thomas MJ, Simpson J, Riley RD, Grant E. The Impact of Home-Based Physiotherapy Interventions on Breathlessness During Activities of Daily Living in Severe Chronic Obstructive Pulmonary Disease: A Systematic Review. Physiotherapy 2010; 96: 108-119. doi:10.1016/j.physio.2009.09.006
  • 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.

2009 

  • 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

2008 

  • Riley RD, Dodd SR, Craig JV, Thompson JR, Williamson PR. Meta-analysis of diagnostic test studies using individual patient data and aggregate data. Stat Med 2008; 27: 6111-6136. doi:10.1002/sim.3441
  • Riley RD, Lambert PC, Staessen JA, Wang J, Gueyffier F, Thijs L, et al. Meta-analysis of continuous outcomes combining individual patient data and aggregate data. Statistics in Medicine 2008, 27: 1870-93. doi:10.1002/sim.3165
  • Riley RD, Thompson JR, Abrams KR. An alternative model for bivariate random-effects meta-analysis when the within-study correlations are unknown. Biostatistics. 2008; 9(1):172-186. doi:10.1093/biostatistics/kxm023

2007

  • Riley RD, Abrams KR, Lambert PC, Sutton AJ, Thompson, JR. An evaluation of bivariate random-effects meta-analysis for the joint synthesis of two correlated outcomes. Statistics in Medicine 2007; 26: 78-97 doi: 10.1002/sim.2524
  • Riley RD, Abrams KR, Sutton AJ, Lambert PC, Thompson JR. Bivariate random-effects meta-analysis and the estimation of between-study correlation. BMC Methodology Research. 2007, 7:3. doi:10.1186/1471-2288-7-3
  • Riley RD, Simmonds MC, Look MP. Evidence synthesis combining individual patient data and aggregate data: a systematic review identified current practice and possible methods. Journal of Clinical Epidemiology 2007: 60; 431-439. doi:10.1016/j.jclinepi.2006.09.009

2006 

  • Sauerbrei W, Holländer N, Riley RD, Altman DG. Evidence based assessment and application of prognostic markers: The long way from single studies to meta-analysis. Communications in Statistics 2006; 35: 1333-42.
  • Dixon-Woods M, Cavers D, Agarwal S, Annandale E, Arthur A, Harvey J, Hsu R, Katbamna S, Olsen R, Smith L, Riley R, Sutton A. Conducting a critical interpretive review of the literature on access to healthcare by vulnerable groups. BMC Medical Research Methodology 2006; 6:35

2005

  • Altman DG, Riley RD: An evidence-based approach to prognostic markers. Nature Clinical Practice Oncology 2005; 2: 466-472.
  • Thompson JR, Minelli C, Abrams KR, Tobin MD, Riley RD: Meta-analysis of genetic studies using Mendelian randomisation - a multivariate approach. Statistics in Medicine 2005, 24: 2241-2254.

Book chapters

  • Riley RD, Abrams KR, Lambert PC, Sutton AJ, Altman DG. Where next for evidence synthesis of prognostic marker studies? Improving the quality and reporting of primary studies to facilitate clinically relevant evidence-based results. In: Auget J-L, Balakrishnan N, Mesbah M, Molenberghs G (eds). Advances in statistical methods for the health sciences. Birkhäuser, 2006. Boston.

Commentaries & letters

  • Riley RD. Commentary: Like it and lump it? Meta-analysis using individual participant data. Int J Epi 39 (5): 1359-1361. doi: 10.1093/ije/dyq129
  • Riley RD, Ridley G, Williams K, Altman DG, Hayden J, de Vet HC. Prognosis research: toward evidence-based results and a Cochrane methods group. J Clin Epidemiol 2007;60(8):863-5

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