Assumption-Lean (Causal) Modelling and Estimation: A Paradigm Shift from Traditional Statistical Modelling

Adaptive learning and testing for causal mechanism

Assumption-lean modeling of repeated measures data

Causal estimands and estimation for randomized clinical trials with intercurrent events: addressing extrapolation

Causal inference for observational HIV/AIDS studies

Causal inference methods to optimize clinical decision-making in treatment initiation based on routinely collected data.

CONTRIBUTION OF AIR POLLUTION AND OVERWEIGHT TO NON-COMMUNICABLE DISEASES IN BELGIUM: ADDRESSING THE LIMITATIONS OF OBSERVATIONAL STUDIES

Debiased machine learning

Doctoral project Fanghong Zhang

Doctoral project Jan Buyse

Doctoral project Josephina Argyrou

Doctoral project Karel Vermeulen

Doctoral project Karl Mertens

Doctoral project Oliver Dukes

Doctoral project Tim De Craecker

Doctoral project Võ Tẩt Thẳng

Doctoral project Wout Waterschoot

Optimal debiased machine learning

Optimizing treatment effect estimation in randomized trials by leveraging baseline covariates and early read-outs

AI-generated synthetic health data in oncology: opportunities and pitfalls

Doctoral project Haeike Josephy

Doctoral project Mohamed Tamer Abdallah Gomah Osman

Doctoral project Sjouke Vandenberghe

Doctoral project Tim De Craecker

Assumption-lean causal modeling

Bias-reduced double-robust estimation

BOF staff support in the framework of an ERC-Grant

Causal inference in observational HIV/AIDS studies.

Center for Statistics

Data-adaptive causal inference under weak assumptions

Dealing with effect decomposition and intermediate confounding in causal mediation analysis

Development of a data-informed causal expert system for personalized treatment recommendations

Honest data-adaptive inference for treatment effects

Methods in Research on Research (MiRoR) / Estimation of causal effects from observational studies: how results obtained from different causal inference methods can be integrated in a meta-analyses approa

Offline and online evaluation of medical treatment decision strategies based on large scale electronic health registers

Optimal causal learning using electronic health records

Optimal estimation of nuisance paramters and models in causal inference

Powerful methods for detecting gene-gene interactions

Semiparametric mixed models for the analysis of genome wide expression data

Structural nested models for the effect of a time-varying exposure on dichtomous outcomes and survival outcomes

Dealing with multiple mediators in causal mediation analysis

Leveraging Big Data To Improve Healthcare Decision-Making

Modelling the impact of microbicides on HIV incidence and prevalence in Mombasa, Kenya

Multilevel causal mediation analysis of multiple longitudinal mediators with unknown causal structure