Dr Rhian Daniel

Reader in Medical Statistics

School of Medicine

: danielr8@cardiff.ac.uk
: 306c, Neuadd Meirionnydd, University Hospital of Wales, Heath Park, Cardiff, CF14 4YS

: Welsh speaking
: Media commentator
: Available for postgraduate supervision

I am a statistician with a particular focus on methods for learning about cause-effect relationships from observational data. I am especially interested in situations, such as when attempting to learn about the joint effects of sequential exposures in the presence of time-dependent confounding, or when attempting to disentangle path-specific causal effects, where standard regression methods are known to be valid only under highly unrealistic assumptions, but where alternative, so-called "causal inference", methods rely on weaker assumptions and hence can deliver substantially more reliable inferences with respect to the question of scientific interest.

I am interested in the development, dissemination and application of these methods.

I hold a Sir Henry Dale fellowship from the Wellcome Trust and the Royal Society on the topic Statistical methods for studying multidimensional mediators of genetic associations with chronic diseases. The methodological developments entailed in this fellowship will extend causal mediation analysis to settings with high-dimensional mediators, by incorporating machine learning methods.

My current/recent applied collaborations include work on socio-economic disparities in breast cancer survival, intergenerational patterns of eating disorder behaviours, and the efficacy of treatments given to patients with cystic fibrosis.

Having recently (June 2017) joined the Division of Population Medicine, I look forward to collaborating with my new colleagues on, among other things, the development and application of causal inference methods to the analysis of routinely-collected data.

Education and qualifications

2009: PhD ("On aspects of robustness and sensitivity in missing data methods"; supervisor: Mike Kenward) London School of Hygiene and Tropical Medicine, London, UK
2005: MSc (Medical Statistics) London School of Hygiene and Tropical Medicine, London, UK
2004: Certificate of Advanced Studies (Mathematics) Queens' College, Cambridge, UK
2003: BA (Mathematics) Queens' College, Cambridge, UK

Career overview

2017 - present: Reader, Division of Population Medicine, Cardiff University
2015 - 2017: Lecturer / Assistant Professor and Sir Henry Dale Fellow, Medical Statistics Department, London School of Hygiene and Tropical Medicine
2013 - 2015: Lecturer, Medical Statistics Department, London School of Hygiene and Tropical Medicine
2011 - 2013: Research Fellow, Medical Statistics Department, London School of Hygiene and Tropical Medicine
2008 - 2011: Research Fellow, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine

Professional memberships

Royal Statistical Society
International Biometrics Society

2020

Muller, I.et al. 2020. CATS II long-term anthropometric and metabolic effects of maternal sub-optimal thyroid function in offspring and mothers. Journal of Clinical Endocrinology and Metabolism 105(7), article number: dgaa129. (10.1210/clinem/dgaa129)
White, J.et al. 2020. Diffusion of effects of the ASSIST school-based smoking prevention intervention to non-participating family members: a randomised controlled trial. Addiction 115(5), pp. 986-991. (10.1111/add.14862)
McQuire, C.et al. 2020. The causal web of fetal alcohol spectrum disorders: a review and causal diagram. European Child and Adolescent Psychiatry 29, pp. 575-594. (10.1007/s00787-018-1264-3)
Aalen, O. O.et al. 2020. Time-dependent mediators in survival analysis: Modeling direct and indirect effects with the additive hazards model. Biometrical Journal 62(3), pp. 532-549. (10.1002/bimj.201800263)

2019

Hurt, L.et al. 2019. Mild-to-moderate renal pelvis dilatation identified during pregnancy and hospital admissions in childhood: an electronic birth cohort study in Wales, UK. PLoS Medicine 16(7), article number: e1002859. (10.1371/journal.pmed.1002859)
Carter, D.et al. 2019. The impact of a cash transfer programme on tuberculosis treatment success rate: A quasi-experimental study in treatment success rate: A quasi-experimental study in Brazil. BMJ Global Health 4, article number: e001029. (10. 1136/bmjgh- 2018- 001029)
Newsome, S.et al. 2019. Investigating the effects of long-term dornase alfa use on lung function using registry data. Journal of Cystic Fibrosis 18(18), pp. 110-117. (10.1016/j.jcf.2018.08.004)

2018

Micali, N.et al. 2018. Maternal pre-pregnancy weight status and adolescent eating disorder behaviors: a longitudinal study of risk pathways. Epidemiology 29(4), pp. 579-589. (10.1097/EDE.0000000000000850)
Newsome, S., Keogh, R. and Daniel, R. 2018. Estimating long-term treatment effects in observational data: a comparison of the performance of different methods under real-world uncertainty. Statistics in Medicine 37(15), pp. 2367-2390. (10.1002/sim.7664)
Keogh, R. H.et al. 2018. Analysis of longitudinal studies with repeated outcome measures: adjusting for time-dependent confounding using conventional methods. American Journal of Epidemiology 187(5), pp. 1085-1092. (10.1093/aje/kwx311)
Daniel, R. 2018. Double robustness. In: Wiley StatsRef: Statistics Reference Online. John Wiley & Sons, Ltd

2017

Devakumar, D.et al. 2017. Socioeconomic determinants of growth in a longitudinal study in Nepal. Maternal & Child Nutrition, article number: e12462. (10.1111/mcn.12462)
Vansteelandt, S. and Daniel, R. M. 2017. Interventional effects for mediation analysis with multiple mediators. Epidemiology 28(2), pp. 258-265. (10.1097/EDE.0000000000000596)
Bijlsma, M. J.et al. 2017. An assessment and extension of the mechanism-based approach to the identification of age-period-cohort models. Demography 54(2), pp. 721-743. (10.1007/s13524-017-0562-6)
Daniel, R. M., De Stavola, B. L. and Vansteelandt, S. 2017. The formal approach to quantitative causal inference in epidemiology: misguided or misrepresented?. International Journal of Epidemiology 45(6), pp. 1817-1829. (10.1093/ije/dyw227)
Daniel, R. 2017. G-computation formula. In: Wiley StatsRef: Statistics Reference Online. Wiley Online Library, (10.1002/9781118445112)
Daniel, R. 2017. Double Robustness. In: Wiley StatsRef: Statistics Reference Online. Wiley Online Library, (10.1002/9781118445112.stat08068)

2016

De Stavola, B. L. and Daniel, R. 2016. Incorporating concepts and methods from causal inference into life course epidemiology. International Journal of Epidemiology 45(4), pp. 1006-1010. (10.1093/ije/dyw103)
Li, R., Daniel, R. and Rachet, B. 2016. How much do tumor stage and treatment explain socioeconomic inequalities in breast cancer survival? Applying causal mediation analysis to population-based data. European Journal of Epidemiology 31(6), pp. 603-611. (10.1007/s10654-016-0155-5)
Greenland, S., Daniel, R. and Pearce, N. 2016. Outcome modelling strategies in epidemiology: traditional methods and basic alternatives. International Journal of Epidemiology 45(2), pp. 565-575. (10.1093/ije/dyw040)
Kahan, B. C.et al. 2016. A comparison of methods to adjust for continuous covariates in the analysis of randomised trials. BMC Medical Research Methodology 16, article number: 42. (10.1186/s12874-016-0141-3)
Keogh, R.et al. 2016. Medication use in early-HD participants in track-HD: an investigation of its effects on clinical performance. PLoS Currents 2016(1), article number: Jan 11. (10.1371/currents.hd.8060298fac1801b01ccea6acc00f97cb)

2015

Burgess, S.et al. 2015. Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways. International Journal of Epidemiology 44(2), pp. 484-495. (10.1093/ije/dyu176)
Daniel, R. M.et al. 2015. Causal mediation analysis with multiple mediators. Biometrics 71(1), pp. 1-14. (10.1111/biom.12248)
De Stavola, B. L.et al. 2015. Mediation analysis with intermediate confounding: structural equation modeling viewed through the causal inference lens. American Journal of Epidemiology 181(1), pp. 64-80. (10.1093/aje/kwu239)

2014

Vansteelandt, S. and Daniel, R. 2014. On regression adjustment for the propensity score. Statistics in Medicine 33(23), pp. 4053-4072. (10.1002/sim.6207)
Jairath, V.et al. 2014. Poor outcomes in hospitalized patients with gastrointestinal bleeding: impact of baseline risk, bleeding severity, and process of care. The American Journal of Gastroenterology 109(10), pp. 1603-1612. (10.1038/ajg.2014.263)
Westreich, D. and Daniel, R. 2014. Commentary: Berkson’s fallacy and missing data. International Journal of Epidemiology 43(2), pp. 524-526. (10.1093/ije/dyu023)

2013

Daniel, R. and Tsiatis, A. A. 2013. Efficient estimation of the distribution of time to composite endpoint when some endpoints are only partially observed. Lifetime Data Analysis 19(4), pp. 513-546. (10.1007/s10985-013-9261-9)
Floyd, S.et al. 2013. Analysis of tuberculosis prevalence surveys: new guidance on best-practice methods. Emerging Themes in Epidemiology 10, article number: 10. (10.1186/1742-7622-10-10)
Millett, E. R. C.et al. 2013. Incidence of community-acquired lower respiratory tract infections and pneumonia among older adults in the United Kingdom: a population-based study. PLoS ONE 8(9), article number: e75131. (10.1371/journal.pone.0075131)
Daniel, R.et al. 2013. Methods for dealing with time-dependent confounding. Statistics in Medicine 32(9), pp. 1584-1618. (10.1002/sim.5686)

2012

Brewer, N.et al. 2012. Which factors account for the ethnic inequalities in stage at diagnosis and cervical cancer survival in New Zealand?. Cancer Epidemiology 36(4), pp. e251-e257. (10.1016/j.canep.2012.03.005)
Daniel, R.et al. 2012. Using causal diagrams to guide analysis in missing data problems. Statistical Methods in Medical Research 21(3), pp. 243-256. (10.1177/0962280210394469)
Daniel, R. and Kenward, M. G. 2012. A method for increasing the robustness of multiple imputation. Computational Statistics & Data Analysis 56(6), pp. 1624-1643. (10.1016/j.csda.2011.10.006)
De Stavola, B. L. and Daniel, R. 2012. Marginal structural models: the way forward for life-course epidemiology?. Epidemiology 23(2), pp. 233-237. (10.1097/EDE.0b013e318245847e)

2010

Santhakumaran, S.et al. 2010. Polygyny and symmetric concurrency: comparing long-duration sexually transmitted infection prevalence using simulated sexual networks. Sexually Transmitted Infections 86(7), pp. 553-558. (10.1136/sti.2009.041780)
White, I. R., Daniel, R. and Royston, P. 2010. Avoiding bias due to perfect prediction in multiple imputation of incomplete categorical variables. Computational Statistics & Data Analysis 54(10), pp. 2267-2275. (10.1016/j.csda.2010.04.005)

2006

Cheung, Y. B., Daniel, R. and Ng, G. Y. 2006. Response and non-response to a quality-of-life question on sexual life: a case study of the simple mean imputation method. Quality of Life Research 15(9), pp. 1493-1501. (10.1007/s11136-006-0004-1)

Areas of expertise

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