Research fellow

Prof. Dr. Vanessa Didelez

Curriculum vitae

since July 2016 Professor of Statistics and Causal Inference, University of Bremen, and Department of Biometry and Data Management, Leibniz Institute for Prevention Research and Epidemiology - BIPS (Deputy Head of Department)

Presentation "Causal reasoning in survival and time-to-event analyses" at the Online Causal Inference Seminar

2018-2020: Principal investigator, DFG grant "Causal Discovery for Cohort Data"

2015-2018: CoIlaborator on MRC grant “Development of a multilevel and mixture-model framework for modelling epigenetic changes over time”

2013-2023: Collaborator on MRC Integrative Epidemiology Unit, Theme 3: "Statistical and Econometric Methodology"

2013- June 2016: Reader in Statistics at the School of Mathematics, University of Bristol

2011-2013: Leverhulme Research Fellowship “Statistical models and methods for complex causal inference”

2009-2013: Senior Lecturer at the School of Mathematics, University of Bristol

2007-2010: CoI on MRC grant “Inferring epidemiological causality using Mendelian Randomisation”

2007-2009: Lecturer at the School of Mathematics, University of Bristol

2001-2007: Lecturer at the Department of Statistical Science, University College London

Dec 2000: PhD (Dr rer.nat.) at the Department of Statistics, University of Dortmund, Germany

1997-2000: Research Assistant at the Department of Statistics, University of Munich, Germany

1996: Diploma in "Statistics with Psychology" at the Department of Statistics, University of Dortmund, Germany




Selected publications

  • Articles with peer-review

  • Andrews R, Didelez V. Insights into the cross-world independence assumption of causal mediation analysis. Epidemiology. 2021;32(2):209-219.
  • Stensrud MJ, Young JG, Didelez V, Robins JM, Hernán MA. Separable effects for causal inference in the presence of competing events. Journal of the American Statistical Association. 2021; (Epub 2020 May 15).
  • Aalen OO, Stensrud MJ, Didelez V, Daniel R, Roysland K, Strohmaier S. Time-dependent mediators in survival analysis: Modeling direct and indirect effects with the additive hazards model. Biometrical Journal. 2020;62(3):532-549.
  • Foraita R, Friemel J, Günther K, Behrens T, Bullerdiek J, Nimzyk R, Ahrens W, Didelez V. Causal discovery of gene regulation with incomplete data. Journal of the Royal Statistical Society. Series A (Statistics in Society). 2020;183(4):1747-1775.
  • Sheehan N, Didelez V. Epidemiology, genetic epidemiology and Mendelian randomisation: More need than ever to attend to detail. Human Genetics. 2020;139(1):121-136.
  • Witte J, Henckel L, Maathuis MH, Didelez V. On efficient adjustment in causal graphs. Journal of Machine Learning Research. 2020;21(246):1-45.
  • Didelez V. Defining causal mediation with a longitudinal mediator and a survival outcome. Lifetime Data Analysis. 2019;25(4):593-610. (This paper was one of 2020’s top downloaded Lifetime Data Analysis research articles.).
  • Witte J, Didelez V. Covariate selection strategies for causal inference: Classification and comparison. Biometrical Journal. 2019;61(5):1270-1289.
  • Phillippo DM, Dias S, Ades AE, Didelez V, Welton NJ. Sensitivity of treatment recommendations to bias in network meta-analysis. Journal of the Royal Statistical Society. Series A (Statistics in Society). 2018;181(3):843-867.
  • Vansteelandt S, Didelez V. Improving the robustness and efficiency of covariate-adjusted linear instrumental variable estimators. Scandinavian Journal of Statistics, Theory and Applications. 2018;45(4):941-961.
  • Farewell D, Huang C, Didelez V. Ignorability for general longitudinal data. Biometrika. 2017;104(2):317-326.
  • Contributions to books and proceedings

  • Didelez V. Causal concepts and graphical models. In: Maathuis M, Drton M, Lauritzen SL, Wainwright M, editors. Handbook of graphical models. Boston: CRC Press. 2018. S. 353-380.
  • Didelez V, Evans R. Causal inference from case-control studies. In: Borgan O, Breslow N, Chatterjee N, Gail M, Scott A, Wild C, editors. Handbook of statistical methods for case-control studies. Boca Raton: Chapman & Hall/CRC. 2018. S. 87-115.
  • Commentaries

  • Didelez V. Comment: Invariance, Causality and Robustness. Statistical Science. 2020;35(3):427-429.

For further publications please follow this link:

Prizes and awards

  • Invited participant Simons Institute Program on Causality
    University of California, Simons Institue for the Theory of Computing, Berkeley, USA (2022)
  • Eingeladene Teilnehmerin, Konferenz "Foundations and New Horizons for Causal Inference", Mai 2019
    Mathematical Research Institute Oberwolfach (2019)
  • Eingeladene Rednerin und Teilnehmerin, Workshop und 1-monatiger Forschungsaufenthalt
    Centre de Recherches Mathematiques (CRM) in Montreal/Canada (2016)
  • Eingeladene IMS Medallion lecture at the 9th World Congress of Probability and Statistics, Toronto
    Institute of Mathematical Statistics (IMS), Beachwood, Ohio/USA (2016)
  • Invited participant at program "High-Dimensional Causal Inference and its Application to Genetics"
    Centre de Recherches Mathématiques (CRM), University of Montréal, Canada (2016)
  • Medallion Lecture
    Institute of Mathematical Statistics (2015)

The responsibility for the content of this page lies with Vanessa Didelez.