Prof. Vanessa Didelez

Weitere Informationen:

Awards and Memberships:

Mitglied der ISCB und der IBC
Action Editor Journal of Machine Learning Research
Scientific Program Chair Causal Learning and Reasoning (CLeaR2024)
Scientific Program Chair ISCB 2025

Ökosystem

Mitglied des Wissenschaftsschwerpunkts "Minds, Media, Machines"

Wissenschaftliche Mitarbeiterin Abteilung Biometrie und EDV

Mitglied des Arbeitsprogramms Lifespan AI

Mitglied des Data Science Center (DSC)

Publikationen

2010 // journal-article

Identifying the consequences of dynamic treatment strategies: A decision theoretic overview

Statistics Surveys

https://doi.org/10.1214/10-ss081

2010 // journal-article

Graphical models for inference under outcome dependent sampling

Statistical Science

https://doi.org/10.1214/10-sts340

2010 // journal-article

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

DOI: 10.1002/sim.4048

2008 // journal-article

Graphical models for marked point processes based on local independence

Journal of the Royal Statistical Society, Series B

https://doi.org/10.1111/j.1467-9868.2007.00634.x

2008 // journal-article

Mendelian randomisation and causal inference in observational epidemiology

PLoS medicine

DOI: 10.1371/journal.pmed.0050177

2008 // book-chapter

Identifying optimal sequential decisions

Proceedings of the 24th Annual conference on Uncertainty in Artificial Intelligence

DOI:

Aug 2007 // journal-article

Mendelian randomization as an instrumental variable approach to causal inference

Statistical Methods in Medical Research

DOI:

2007 // journal-article

Graphical models for composable finite Markov processes

Scandinavian Journal of Statistics

https://doi.org/10.1111/j.1467-9469.2006.00528.x

2007 // journal-article

Mendelian randomization as an instrumental variable approach to causal inference

Statistical methods in medical research

DOI: 10.1177/0962280206077743

2007 // journal-article

Discussion on the paper by Diggle, Farewell and Henderson

Applied statistics

DOI:

2007 // book-chapter

Mendelian randomisation: Why epidemiology needs a formal language for causality

Causality and Probability in the Sciences

DOI:

2007 // book-chapter

Statistical causality

Consilience. Interdisplinary Communications

DOI:

2007 // journal-article

Discussion of 'Analysis of longitudinal data with drop-out: objectives, assumptions and a proposal' bei Diggle, Farewell, Henderson

Journal of the Royal Statistical Society, Series C (Applied Statistics)

DOI:

Mar 2006 // journal-article

Modifications of the Bonferroni-Holm procedure for a multi-way ANOVA

Statistical Papers

Vanessa Didelez; Iris Pigeot; Patricia Walter

DOI: 10.1007/s00362-005-0283-6

2006 // book-chapter

Direct and indirect effects of sequential treatments

Proceedings of the 22nd Annual conference on Uncertainty in Artificial Intelligence

DOI:

2006 // edited-book

Direct and indirect effects of sequential treatments

In Proc. 22nd Annual Conference on Uncertainty in Artificial Intelligence (2006), edited by R. Dechter and T. S. Richardson. AUAI Press, Arlington, Virginia, 138-146

DOI:

2006 // journal-article

Discussion of 'Semiparametric analysis of case series data' by Farrington and Whitaker

Journal of the Royal Statistical Society, Series C (Applied Statistics)

DOI:

Jul 2005 // journal-article

Latent variable analysis and partial correlation graphs for multivariate time series

Statistics & Probability Letters

Roland Fried; Vanessa Didelez

DOI: 10.1016/j.spl.2005.04.002

2005 // journal-article

Latent variable analysis and partial correlation graphs for multivariate time series

Statistics & probability letters

DOI:

2005 // book-chapter

Partial correlation graphs and dynamic latent variables for physiological time series

Innovations in classification, data science, and information systems

DOI:

2005 // other

Partial Correlation Graphs and Dynamic Latent Variables for Physiological Time Series

Innovations in Classification, Data Science, and Information Systems

https://doi.org/10.1007/3-540-26981-9_30

2004 // journal-article

BOOK REVIEWS: 2

Biometrics

Vanessa Didelez

DOI: 10.1111/j.0006-341x.2004.262_2.x

2004 // journal-article

Collapsibility of Graphical CG-Regression Models

Scandinavian Journal of Statistics

Vanessa Didelez; David Edwards

DOI: 10.1111/j.1467-9469.2004.00405.x

Jun 2003 // journal-article

Decomposability and selection of graphical models for multivariate time series

Biometrika

https://doi.org/10.1093/biomet/90.2.251

May 2003 // book-chapter

Comments on graphical models for stochastic processes

Highly structured stochastic systems

DOI:

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Prof. Vanessa Didelez

Ökosystem

Publikationen

Identifying the consequences of dynamic treatment strategies: A decision theoretic overview

Graphical models for inference under outcome dependent sampling

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

Graphical models for marked point processes based on local independence

Mendelian randomisation and causal inference in observational epidemiology

Identifying optimal sequential decisions

Mendelian randomization as an instrumental variable approach to causal inference

Graphical models for composable finite Markov processes

Mendelian randomization as an instrumental variable approach to causal inference

Discussion on the paper by Diggle, Farewell and Henderson

Mendelian randomisation: Why epidemiology needs a formal language for causality

Statistical causality

Discussion of 'Analysis of longitudinal data with drop-out: objectives, assumptions and a proposal' bei Diggle, Farewell, Henderson

Modifications of the Bonferroni-Holm procedure for a multi-way ANOVA

Direct and indirect effects of sequential treatments

Direct and indirect effects of sequential treatments

Discussion of 'Semiparametric analysis of case series data' by Farrington and Whitaker

Latent variable analysis and partial correlation graphs for multivariate time series

Latent variable analysis and partial correlation graphs for multivariate time series

Partial correlation graphs and dynamic latent variables for physiological time series

Partial Correlation Graphs and Dynamic Latent Variables for Physiological Time Series

BOOK REVIEWS: 2

Collapsibility of Graphical CG-Regression Models

Decomposability and selection of graphical models for multivariate time series

Comments on graphical models for stochastic processes

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