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Covariate selection strategies for causal inference: Classification and comparison

Biometrical journal, 2019-09, Vol.61 (5), p.1270-1289

2019

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Mendelian randomization as an instrumental variable approach to causal inference

Statistical methods in medical research, 2007-08, Vol.16 (4), p.309-330

2007

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Longitudinal mediation analysis with multilevel and latent growth models: a separable effects causal approach

BMC medical research methodology, 2024-10, Vol.24 (1), p.248-16, Article 248

2024

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Separable Effects for Causal Inference in the Presence of Competing Events

Journal of the American Statistical Association, 2022-01, Vol.117 (537), p.175-183

2022

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Invited Commentary: Where Do the Causal DAGs Come From?

American journal of epidemiology, 2024-08, Vol.193 (8), p.1075-1078

Didelez, Vanessa

2024

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Mendelian randomisation and causal inference in observational epidemiology

PLoS medicine, 2008-08, Vol.5 (8), p.e177-e177

2008

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Defining causal mediation with a longitudinal mediator and a survival outcome

Lifetime data analysis, 2019-10, Vol.25 (4), p.593-610

Didelez, Vanessa

2019

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Seconder of the vote of thanks to Vansteelandt and Dukes and contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2022-07, Vol.84 (3), p.689-691

Didelez, Vanessa

2022

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A longitudinal causal graph analysis investigating modifiable risk factors and obesity in a European cohort of children and adolescents

Scientific reports, 2024-03, Vol.14 (1), p.6822-6822, Article 6822

2024

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Commentary: Should the analysis of observational data always be preceded by specifying a target experimental trial?

International journal of epidemiology, 2016-12, Vol.45 (6), p.2049-2051

Didelez, Vanessa

2016

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A generalized theory of separable effects in competing event settings

Lifetime data analysis, 2021-10, Vol.27 (4), p.588-631

2021

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Emulierung von „target trials“ mit Real-world-Daten: Ein allgemeines Prinzip, um den Herausforderungen von Beobachtungsdaten zu begegnen

Prävention und Gesundheitsförderung, 2022-07

2022

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The role of psychosocial well-being and emotion-driven impulsiveness in food choices of European adolescents

The international journal of behavioral nutrition and physical activity, 2024-01, Vol.21 (1), p.1-1, Article 1

2024

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Nutzung von Sekundärdaten für die pharmakoepidemiologische Forschung – machen wir das Beste draus

Gesundheitswesen (Bundesverband der Ärzte des Öffentlichen Gesundheitsdienstes (Germany)), 2021-11, Vol.83 (S 02), p.S69-S76

2021

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Perspective on Interviews with Heckman, Pearl, Robins and Rubin

Observational studies, 2022-10, Vol.8 (2), p.95-104

Didelez, Vanessa

2022

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Comment: Invariance, Causality and Robustness

Statistical science, 2020-08, Vol.35 (3), p.427

Didelez, Vanessa

2020

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Graphical models for marked point processes based on local independence

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2008-02, Vol.70 (1), p.245-264

Didelez, Vanessa

2008

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Improving the robustness and efficiency of covariate-adjusted linear instrumental variable estimators

Scandinavian journal of statistics, 2018-12, Vol.45 (4), p.941-961

2018

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Re: Are Target Trial Emulations the Gold Standard for Observational Studies?

Epidemiology (Cambridge, Mass.), 2024-01, Vol.35 (1), p.e3-e3

2024

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Insights into the Cross-world Independence Assumption of Causal Mediation Analysis

Epidemiology (Cambridge, Mass.), 2021-03, Vol.32 (2), p.209-219

2021

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Epidemiology, genetic epidemiology and Mendelian randomisation: more need than ever to attend to detail

Human genetics, 2020-01, Vol.139 (1), p.121-136

2020

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Parameterizing and simulating from causal models

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2024-07, Vol.86 (3), p.535-568

2024

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Authors’ reply to the Discussion of ‘Parameterizing and simulating from causal models

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2024-07, Vol.86 (3), p.582-585

2024

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Multiple imputation and test‐wise deletion for causal discovery with incomplete cohort data

Statistics in medicine, 2022-10, Vol.41 (23), p.4716-4743

2022

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On the logic of collapsibility for causal effect measures

Biometrical journal, 2022-02, Vol.64 (2), p.235-242

2022

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Covariate selection strategies for causal inference: Classification and comparison

Mendelian randomization as an instrumental variable approach to causal inference

Longitudinal mediation analysis with multilevel and latent growth models: a separable effects causal approach

Separable Effects for Causal Inference in the Presence of Competing Events

Invited Commentary: Where Do the Causal DAGs Come From?

Mendelian randomisation and causal inference in observational epidemiology

Defining causal mediation with a longitudinal mediator and a survival outcome

Seconder of the vote of thanks to Vansteelandt and Dukes and contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’

A longitudinal causal graph analysis investigating modifiable risk factors and obesity in a European cohort of children and adolescents

Commentary: Should the analysis of observational data always be preceded by specifying a target experimental trial?

A generalized theory of separable effects in competing event settings

Emulierung von „target trials“ mit Real-world-Daten: Ein allgemeines Prinzip, um den Herausforderungen von Beobachtungsdaten zu begegnen

The role of psychosocial well-being and emotion-driven impulsiveness in food choices of European adolescents

Nutzung von Sekundärdaten für die pharmakoepidemiologische Forschung – machen wir das Beste draus

Perspective on Interviews with Heckman, Pearl, Robins and Rubin

Comment: Invariance, Causality and Robustness

Graphical models for marked point processes based on local independence

Improving the robustness and efficiency of covariate-adjusted linear instrumental variable estimators

Re: Are Target Trial Emulations the Gold Standard for Observational Studies?

Insights into the Cross-world Independence Assumption of Causal Mediation Analysis

Epidemiology, genetic epidemiology and Mendelian randomisation: more need than ever to attend to detail

Parameterizing and simulating from causal models

Authors’ reply to the Discussion of ‘Parameterizing and simulating from causal models

Multiple imputation and test‐wise deletion for causal discovery with incomplete cohort data

On the logic of collapsibility for causal effect measures

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