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Professor Kate Tilling
Professor Kate Tilling
Professor of Medical Statistics
BSc(Warw), MSc(Oxon), PhD(Lond)
My main research interests are in the development and application of statistical methods to causal problems in epidemiology/health services research. Two particular areas are methods for analysis of longitudinal data, and methods for minimising bias due to missing data.
I teach 1st and 4th year medical students, and also contribute to the Short Course Programme.
My main areas of expertise are in methods for analysing exposures and outcomes across the life course, and in methods for dealing with missing data.
I have a mathematical background, an MSc in Applied Statistics and a PhD in epidemiology, together with more than 15 years experience working in academic public health and epidemiology.
I enjoy interpreting and explaining results from more complex statistical methods to other researchers and members of the public and using all forms of the media to effectively promote public health messages.
statistical methodslifecourse methodsmissing dataepidemiology
- Millard, LAC, Davies, NM, Timpson, NJ, Tilling, KM, Flach, PA & Smith, GD, 2015, MR-PheWAS: Hypothesis prioritization among potential causal effects of body mass index on many outcomes, using Mendelian randomization. Scientific Reports, vol 5.
- Lawlor, D, Smith, A, Tilling, K & Nelson, SM, 2015, Live-birth rate associated with repeat in vitro fertilisation treatment cycles. JAMA: The Journal of the American Medical Association.
- Palace, J, Duddy, M, Bregenzer, T, Lawton, M, Zhu, F, Boggild, M, Piske, B, Robertson, NP, Oger, J, Tremlett, H, Tilling, K, Ben-Shlomo, Y & Dobson, C, 2015, Effectiveness and cost-effectiveness of interferon beta and glatiramer acetate in the UK Multiple Sclerosis Risk Sharing Scheme at 6 years: a clinical cohort study with natural history comparator. The Lancet. Neurology.
- Macdonald-Wallis, C, Silverwood, RJ, De Stavola, BL, Inskip, H, Cooper, C, Godfrey, KM, Crozier, SR, Fraser, A, Nelson, SM, Lawlor, D & Tilling, K, 2015, Antenatal blood pressure for prediction of preeclampsia, preterm birth and small-for-gestational age: Development and validation in two general population cohorts. British Medical Journal, vol 351., pp. 1-11
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- Simpkin, AJ, Donovan, JL, Tilling, K, Lane, JA, Martin, RM, Albertsen, PC, Bill-Axelson, A, Carter, HB, Bosch, R, Ferrucci, L, Hamdy, FC, Holmberg, L, Metter, EJ, Neal, DE, Parker, CC & Metcalfe, C, 2016, Prostate specific antigen patterns in US and European populations: comparison of six diverse cohorts. BJU International.
- Kidger, JL, Brockman, R, Tilling, KM, Campbell, RM, Ford, T, Araya, R, King, M & Gunnell, D, 2016, Teachers' wellbeing and depressive symptoms, and associated risk factors: A large cross sectional study in English secondary schools. Journal of Affective Disorders, vol 192., pp. 76-82
- Mars, B, Cornish, R, Heron, J, Boyd, A, Crane, C, Hawton, K, Lewis, G, Tilling, K, Macleod, J & Gunnell, D, 2016, Using Data Linkage to Investigate Inconsistent Reporting of Self-Harm and Questionnaire Non-Response. Archives of suicide research : official journal of the International Academy for Suicide Research., pp. 1-29
- Collin, SM, Norris, T, Nuevo, R, Tilling, K, Joinson, C, Sterne, JAC & Crawley, E, 2016, Chronic Fatigue Syndrome at Age 16 Years. Pediatrics.
- Heron, J, Croudace, TJ, Barker, ED & Tilling, K, 2015, A comparison of approaches for assessing covariate effects in latent class analysis. Longitudinal and Life Course Studies, vol 6., pp. 420-434
- Collin, SM, Tilling, K, Joinson, C, Rimes, KA, Pearson, RM, Hughes, RA, Sterne, JAC & Crawley, E, 2015, Maternal and childhood psychological factors predict chronic disabling fatigue at age 13 years. Journal of Adolescent Health, vol 56., pp. 181-187
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