Vanessa Didelez

Reader in Statistics

(Climbing the Great Wall of China photo.)


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Contact Details
Dr Vanessa Didelez
School of Mathematics,
University of Bristol
University Walk
Bristol BS8 1TW (UK)

Tel : +44 (0)117 928 9852
e-mail: vanessa . didelez "at" bristol (dot) ac "dot" uk



TEACHING

Office hour: by appointment

Graphical Modelling (MATH M6002)

Multivariate Analysis (MATH 30510 / MATH M0510)

Stupid Questions?



RESEARCH WORKSHOPS

Up-coming workshops I am co-organising:

4th Annual UK-CIM 2016 (London)

Past workshops I co-organised:

Just for Info, this one was also interesting and in Bristol: Mendelian Randomisation Conference
3rd UK-CIM 2015: Causal Inference in Health and Social Sciences (Bristol)
The Statistical Contributions of A.Philip Dawid: Causal Inference, Graphical Models and Prediction. (Cambridge, 2015)
1st and 2nd UK-CIMs: 2013 (Manchester) and 2014 (Cambridge): Causal Inference in Health and Social Sciences
Time for Causality - Causal Inference and Dynamic Decisions in Longitudinal Studies, 10-13 April 2012



Research Interests
Google Scholar Profile


PUBLICATIONS (in reverse chronological order)

Research Reports

Robustness and efficiency of covariate adjusted linear instrumental variable estimators, 2015, on arXiv, (with Stijn Vansteelandt)


Refereed Journal Papers

Inequalities on partial correlations in GGMs containing star shapes. Communications in Statistics – Theory and Methods, 2016, DOI: 10.1080/03610926.2014.953696 (with Edmund Jones). (pdf)

Comparison of statistical methods for finding network motifs. Statistical Applications in Genetics and Molecular Biology, 13(4), 403–422 (with Vanna Albieri) (pdf), and supplementary material.

Lack of identi cation in semi-parametric instrumental variable models with binary outcomes. American Journal of Epidemiology, 180(11), 111-119, 2014; (with S.Burgess, R.Granell, T.M.Palmer, J.A.C.Sterne) www-page

Severity of bias of a simple estimator of the causal odds ratio in Mendelian randomization studies. Statistics in Medicine, 32(7), 1246-1258, 2013; (with R.Harbord, J.A.C.Sterne, T.M.Palmer, N.A.Sheehan) (pdf)

Simulating from marginal structural models with time-dependent confounding. Statistics in Medicine, 31(30), 4190-4206, 2012 (with W.Havercroft). (pdf)

On the choice of parameterisation and priors for the Bayesian analyses of Mendelian randomisation studies. Statistics in Medicine, 31(14), 1483-1501, 2012 (with E.Jones, J.Thompson and N.A.Sheehan). (pdf)

Nonparametric bounds for the causal effect in a binary instrumental variable model. The Stata Journal, 11(3), 345-367, 2011 (with T.M.Palmer, N.A.Sheehan, R. Ramsahai). www-page, (pdf)

Instrumental variable estimation of causal risk ratios and causal odds ratios in Mendelian randomization analyses. The American Journal of Epidemiology, 2011, Vol.173, No.12, (with T.M.Palmer, J.A.C.Sterne, R.M.Harbord, D.A.Lawlor, N.A.Sheehan, S.Meng, R.Granell, G.Davey Smith) DOI: 10.1093/aje/kwr026.

Identifying the consequences of dynamic treatment strategies: A decision theoretic overview, Statistics Surveys, 4, 184-231, 2010 (with A.P. Dawid). (pdf)

Graphical models for inference under outcome dependent sampling, Statistical Science, 25, 368-387, 2010 (with S. Kreiner and N. Keiding). (pdf)

A sequential Cox approach for estimating the causal effect of treatment in the presence of time-dependent confounding applied to data from the Swiss HIV Cohort Study, Statistics in Medicine, 2010 (with Gran, J. M.; Roysland, K.; Wolbers, M.; Sterne, J.A.C.; Ledergerber, B.; Furrer, H.; von Wyl, V.; Aalen, O.O.). pdf-file, http://dx.doi.org/10.1002/sim.4048

Assumptions of IV methods for observational epidemiology, Statistical Science, 25, 22-40, 2010 (with S.Meng and N.A.Sheehan). (pdf)

Granger-causality and the effect of interventions in time series, Lifetime Data Analysis, 16, 3-32, 2010 (with M. Eichler). (pdf)

Mendelian randomisation and causal inference in observational epidemiology, PLoS Medicine Vol 5, No 8, e177 doi:10.1371/journal.pmed.0050177, 2008 (with N.A.Sheehan, P.R.Burton, M.D.Tobin). (pdf)

Graphical models for marked point processes based on local independence, Journal of the Royal Statistical Society, Series B, 70, 245-264, 2008. (pdf)

Mendelian randomisation as an instrumental variable approach to causal inference, Statistical Methods in Medical Research, 16, 309-330, 2007 (with N.A.Sheehan). (pdf)

Graphical models for composable finite Markov processes, Scandinavian Journal of Statistics, 34, 169-185, 2007. (pdf)

Modifications of the Bonferroni-Holm procedure for a multiway ANOVA, Statistical Papers, 2006, 47, 181 - 209 (with Iris Pigeot and Patricia Walter). (pdf)

Latent variable analysis and partial correlation graphs for multivariate time series, Statistics and Probability Letters, 2005, 73, 287-296 (with Roland Fried). (pdf)

Collapsibility in graphical CG-regression models, Scandinavian Journal of Statistics, 2004, 31, 535-551 (with David Edwards). (pdf)

Decomposability and selection of graphical models for time series, Biometrika, 2003, 90, pp.251-267 (with Roland Fried). (pdf)

ML- and semiparametric estimation in logistic models with incomplete covariate data, Statistica Neerlandica, 2002, 56, pp.330-345. (pdf)

A comparative analysis of graphical interaction and logistic regression modelling: self-care and coping with a chronic illness in later life, Biometrical Journal, 2002, 44, pp.410-432 (with Iris Pigeot, Kay Dean, Andrew Wister). (pdf)

Maximum likelihood estimation in graphical models with missing values, Biometrika, 1998, 85, 4, pp.960-966 (with Iris Pigeot). (pdf)


Refereed Proceedings

Recovering from selection bias using marginal structure in discrete models, Proceedings of the 31st Annual Conference on Uncertainty in Artifical Intelligence - Causality Workshop, 2015 (with R.J.Evans). (pdf). See also proceedings.

Identifying optimal sequential decisions, Proceedings of the 24th Annual Conference on Uncertainty in Artifical Intelligence, 113-120, 2008 (with A.P.Dawid). (pdf)

Causal reasoning in graphical time series models, in: Proceedings of the 23rd Annual Conference on Uncertainty in Artifical Intelligence, 109-116, 2007 (with M.Eichler). (pdf)

Direct and indirect effects of sequential treatments, in: Proceedings of the 22nd Annual Conference on Uncertainty in Artifical Intelligence, 2006, 138-146 (with A.P.Dawid and S.Geneletti). (pdf)

Asymmetric Separation for Local Independence Graphs, in: Proceedings of the 22nd Annual Conference on Uncertainty in Artifical Intelligence, 2006, 130-137. (pdf)

Partial Correlation Graphs and Dynamic Latent Variables for Physiological Time Series, in: Daniel Baier and Klaus-Dieter Wernecke (eds.): Innovations in Classification, Data Science, and Information Systems. Proc. 27th Annual GfKl Conference, University of Cottbus, March 12 - 14, 2003. Springer-Verlag, Heidelberg-Berlin, 2004, pp.259-266 (with Roland Fried and Vivian Lanius). (pdf)


Others

Commentary: Should the analysis of observational data always be preceded by specifying a target experimental trial? International Journal of Epidemiology, Advance Access published 10 April 2016.

Causal Inference from Case-Control Studies. To appear as chapter in: Handbook of Case-Control Studies (Eds.: N. Breslow, O. Borgan, N. Chatterjee, A. Scott, G. Mitchell), with Robin Evans.

Causal Reasoning for events in continuous time: a decision–theoretic approach, Proceedings of the 31st Annual Conference on Uncertainty in Artifical Intelligence - Causality Workshop, 2015 (Invited Paper). (pdf) See also proceedings.

Instrumental Variables for Epidemiology (with Nuala Sheehan) in: ''Mendelian Randomization: How genes can reveal the biological and environmental causes of disease'' edited by G.Davey-Smith, OUP.

IV Methods for Binary Outcomes (with Frank Windmeijer) in: ''Mendelian Randomization: How genes can reveal the biological and environmental causes of disease'' edited by G.Davey-Smith, OUP.

Discussion of 'Experimental Designs for Identifying Causal Mechanisms' by Imai, Tingley, Yamamoto. JRSS-A, 176, p. 39, 2013. (pdf)

RE: Credible Mendelian randomization studies: approaches for evaluating the instrumental variable assumptions. Letter to American Journal of Epidemiology, 176, 5, p457, 2012. (With T.Palmer, R.Ramsahai, D.Lawlor, N.Sheehan), (pdf).

Assessing dynamic treatment strategies. Chapter 8 in 'Causality: Statistical Perspectives and Applications' (eds.: Berzuini, Dawid, Berardinelli), Wiley, 2012 (with C.Berzuini and A.P. Dawid), (pdf)

Imagine a can opener - the magic of principal stratum analysis. Invited commentary, International Journal of Biostatistics, 2012 (with A.P.Dawid). (pdf)

G-estimation for accelerated failure time models. In: Y.-K. Tu and D.C. Greenwood (eds.), Modern Methods for Epidemiology, Chapter 14, p.243-60, 2012, Springer (with K.Tilling and J.Sterne), (pdf).

Commentary: Can ‘many weak’ instruments ever be ‘strong’? International Journal of Epidemiology, 2011; doi: 10.1093/ije/dyr017 (with N.A.Sheehan). (pdf)

Mendelian randomisation: a tool for assessing causality in observational epidemiology, In: "Genetic Epidemiology" (ed. D.Teare), Methods in Molecular Biology, Vol. 713, Springer Science+Business Media, LLC 2011 (with N.A.Sheehan and S.Meng). (pdf)

Mendelian randomisation: why epidemiology needs a formal language for causality, in: F. Russo and J. Williamson (eds.), Causality and Probability in the Sciences, College Publications London, 2007, (with N.A.Sheehan). (pdf)

Discussion of 'Analysis of longitudinal data with drop-out: objectives, assumptions and a proposal' by Diggle, Farewell, Henderson. JRSS C, Appl.Statist., 2007, 56, Part 5, pp. 536-7, (pdf)

Statistical causality, in: W. Ostreng (ed), Consilience. Interdisciplinary Communications, Centre for Advanced Study, Oslo, 2007. (pdf)

Discussion of 'Semiparametric analysis of case series data' by Farrington and Whitaker. JRSS C, Appl. Statist., 2006, 55, Part 5, p.587, (with Odd Aalen) (pdf)

Graphical Models and Sequential Decisions, Proceedings of the 54th Session of the ISI (invited lecture), 2003. (pdf)

Comments on graphical models for stochastic processes, in Green, P., Hjort, N. and Richardson, S. (eds.): Highly structured stochastic systems, 2003, University Press, Oxford. (pdf)

Graphical Models for Event History Analysis based on Local Independence, PhD Thesis, 2000, Logos, Berlin. (pdf)






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    Page last updated: March 2016.