Vanessa Didelez
Vanessa Didelez
Professor of Statistics, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen
Verified email at - Homepage
Cited by
Cited by
Mendelian randomization as an instrumental variable approach to causal inference
V Didelez, N Sheehan
Statistical Methods in Medical Research 16 (4), 309-330, 2007
Mendelian randomisation and causal inference in observational epidemiology
NA Sheehan, V Didelez, PR Burton, MD Tobin
PLoS medicine 5 (8), e177, 2008
Instrumental variable estimation of causal risk ratios and causal odds ratios in Mendelian randomization analyses
TM Palmer, JAC Sterne, RM Harbord, DA Lawlor, NA Sheehan, S Meng, ...
American Journal of Epidemiology 173 (12), 1392-1403, 2011
Assumptions of IV methods for observational epidemiology
V Didelez, S Meng, NA Sheehan
Statistical Science 25 (1), 22-40, 2010
Direct and indirect effects of sequential treatments
V Didelez, P Dawid, S Geneletti
Proceedings of the 22nd Annual Conference on Uncertainty in Artifical …, 2006
Graphical models for marked point processes based on local independence
V Didelez
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2008
Identifying the consequences of dynamic treatment strategies: A decision-theoretic overview
AP Dawid, V Didelez
Statistics Surveys 4, 184-231, 2010
On Granger causality and the effect of interventions in time series
M Eichler, V Didelez
Lifetime Data Analysis 16 (1), 3-32, 2010
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
JM Gran, K Rřysland, M Wolbers, V Didelez, JAC Sterne, B Ledergerber, ...
Statistics in Medicine 29 (26), 2757-2768, 2010
Graphical models for inference under outcome-dependent sampling
V Didelez, S Kreiner, N Keiding
Statistical Science 25 (3), 368-387, 2010
Covariate selection strategies for causal inference: classification and comparison
J Witte, V Didelez
Biometrical Journal, 2018
Separable effects for causal inference in the presence of competing events
MJ Stensrud, JG Young, V Didelez, JM Robins, MA Hernán
Journal of the American Statistical Association 117 (537), 175-183, 2022
Defining causal mediation with a longitudinal mediator and a survival outcome
V Didelez
Lifetime Data Analysis 25, 593 - 610, 2019
Causal reasoning in graphical time series models
M Eichler, V Didelez
Proceedings of the 23rd Annual Conference on Uncertainty in Artifical …, 2007
On efficient adjustment in causal graphs
J Witte, L Henckel, MH Maathuis, V Didelez
Journal of Machine Learning Research 21 (246), 1−45, 2020
Graphical models for composable finite Markov processes
V Didelez
Scandinavian Journal of Statistics 34 (1), 169-185, 2007
Sensitivity of treatment recommendations to bias in network meta-analysis
DM Phillippo, S Dias, AE Ades, V Didelez, NJ Welton
Journal of the Royal Statistical Society Series A: Statistics in Society 181 …, 2018
Severity of bias of a simple estimator of the causal odds ratio in Mendelian randomization studies
RM Harbord, V Didelez, TM Palmer, S Meng, JAC Sterne, NA Sheehan
Statistics in Medicine 32 (7), 1246-1258, 2013
Time-dependent mediators in survival analysis: Modelling direct and indirect effects with the additive hazards model
OO Aalen, MJ Stensrud, V Didelez, R Daniel, K Rřysland, S Strohmaier
Biometrical Journal 62, 532 - 549, 2020
Epidemiology, genetic epidemiology and Mendelian randomisation: more need than ever to attend to detail
NA Sheehan, V Didelez
Human Genetics 139, 121 - 136, 2020
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