Jean Hamilton BSc (Lancaster), MSc (Lancaster), PhD (Bristol)
Research Associate
HEDS, ScHARR
University of Sheffield
Regent Court, 30 Regent Street
Sheffield, S1 4DA
Office: 1012
Tel: (+44) (0)114 222 5447
Fax: (+44) (0)114 222 0749
E-mail: jean.hamilton@sheffield.ac.uk
ORCiD: 0000-0003-3326-9842
Biography
I joined ScHARR (HEDS) in October 2014 as a Research Associate in Statistics. Prior to this, I have held research positions at Massey University (New Zealand) and the University of Cambridge. I completed my MSc. in Medical Statistics at Lancaster University, and PhD at the University of Bristol.
Research interests
My research interests include
- Network meta-analysis
- Statistical methods in health economics
- Deriving and assessing risk predictions
- Multi-scale methods and time series
Journal articles
- Hamilton J, Nunes MA, Knight MI & Fryzlewicz P (2017) Complex-valued wavelet lifting and applications. Technometrics, 0-0. View this article in WRRO
- Sadler S, Angus C, Gavens L, Gillespie D, Holmes J, Hamilton J, Brennan A & Meier P (2016) Understanding the alcohol harm paradox: an analysis of sex- and condition-specific hospital admissions by socioeconomic group for alcohol-associated conditions in England.. Addiction. View this article in WRRO
- Kearns B, Pandor A, Stevenson M, Hamilton J, Chambers D, Clowes M, Graham J & Kumar MS (2016) Cabazitaxel for Hormone-Relapsed Metastatic Prostate Cancer Previously Treated With a Docetaxel-Containing Regimen: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.. Pharmacoeconomics. View this article in WRRO
- Davis S, Martyn-St James M, Sanderson J, Stevens J, Goka E, Rawdin A, Sadler S, Wong R, Campbell F, Stevenson M, Strong M, Selby P & Gittoes N (2016) A systematic review and economic evaluation of bisphosphonates for the prevention of fragility fractures. Health Technology Assessment, 20(78), 1-406. View this article in WRRO
- Sanderson J (2016) Clinical effectiveness of bisphosphonates for the prevention of fragility fractures: A systematic review and network meta-analysis. BONE, 89, 52-58. View this article in WRRO
- Lash GE, Bulmer JN, Li TC, Innes BA, Mariee N, Patel G, Sanderson J, Quenby S & Laird SM (2016) Standardisation of uterine natural killer (uNK) cell measurements in the endometrium of women with recurrent reproductive failure. Journal of Reproductive Immunology, 116, 50-59. View this article in WRRO
- Stevenson M, Pandor A, Martyn-St James M, Rafia R, Uttley L, Stevens J, Sanderson J, Wong R, Perkins GD, McMullan R & Dark P (2016) Sepsis: the LightCycler SeptiFast Test MGRADE®, SepsiTest™ and IRIDICA BAC BSI assay for rapidly identifying bloodstream bacteria and fungi - a systematic review and economic evaluation.. Health Technol Assess, 20(46), 1-246. View this article in WRRO
- Carroll C, Tappenden P, Rafia R, Hamilton J, Chambers D, Clowes M, Durrington P, Qureshi N & Wierzbicki AS (2016) Evolocumab for Treating Primary Hypercholesterolaemia and Mixed Dyslipidaemia: An Evidence Review Group Perspective of a NICE Single Technology Appraisal. PharmacoEconomics, 35(5), 537-547.
- Sanderson J, Sudoyo H, Karafet TM, Hammer MF & Cox MP (2015) Reconstructing Past Admixture Processes from Local Genomic Ancestry Using Wavelet Transformation. Genetics, 200(2), 469-481. View this article in WRRO
- Sanderson J, Thompson SG, White IR, Aspelund T & Pennells L (2013) Derivation and assessment of risk prediction models using case-cohort data. BMC Medical Research Methodology, 13(1). View this article in WRRO
- Anchala R, Pinto MP, Shroufi A, Chowdhury R, Sanderson J, Johnson L, Blanco P, Prabhakaran D & Franco OH (2012) The role of Decision Support System (DSS) in prevention of cardiovascular disease: a systematic review and meta-analysis.. PloS one, 7(10), e47064.
- Buitrago-Lopez A, Sanderson J, Johnson L, Warnakula S, Wood A, Di Angelantonio E & Franco OH (2011) Chocolate consumption and cardiometabolic disorders: systematic review and meta-analysis. BMJ, 343(aug26 1), d4488-d4488.
- Sanderson J, Fryzlewicz P & Jones MW (2010) Estimating linear dependence between nonstationary time series using the locally stationary wavelet model. Biometrika, 97(2), 435-446.