Project description
Revolutionising statistical modelling
Statistical modelling plays a vital role across many sectors, enhancing the quality of data analysis, improving readability and comprehension, and offering key insights into collected data. The ERC-funded ACME project aims to revolutionise statistical modelling by introducing a cutting-edge, transformative paradigm that significantly improves data analysis. The project will develop an assumption-lean modelling framework designed to maximise interpretability and minimise bias, even in the presence of model misspecification. Researchers will explore and apply debiased learning to create new estimators and strategies that address current limitations. Ultimately, the results have the potential to advance numerous empirical sciences by providing powerful new tools that could drive significant breakthroughs.
Objective
I propose a cutting-edge and transformative paradigm for statistical modelling that is crucial to enhance the quality of data analyses. Leveraging my expertise in causal inference and semiparametric statistics, I will establish the fundamental principles of a comprehensive estimation theory, which maps model parameters onto generic, interpretable, model-free estimands (e.g. association or effect measures) with favourable efficiency bound, and harnesses the power of debiased (statistical/machine) learning techniques to estimate these. My core objective is to develop a flexible and accessible data modelling framework, called ‘assumption-lean modelling’. This framework will deliver minimal bias and maximal interpretability, even in the presence of model misspecification, along with honest confidence bounds that account for model uncertainty.
Debiased learning is at the core of this research. While gaining popularity, a rigorous scientific optimality theory is lacking. I shall draw on my expertise in (bias-reduced) double robust estimation to develop optimal debiased learning estimators. These utilize learners that optimize strategically chosen loss functions to achieve low variance and high stability, along with confidence intervals that are valid under weak conditions on the learners.
I will connect to timely, exciting developments in statistics, such as debiased learning of function-valued parameters and the construction of confidence bounds for such parameters. I will offer novel avenues into these problems by incorporating the assumption-lean modelling principles and connecting to real-world needs.
I will develop assumption-lean modelling strategies to tackle significant challenges in causal modelling, including target trial emulation, causal mediation analysis, and statistical modelling of dependent outcomes. I will deliver methods with potential impact on all empirical sciences, as well as on the foundations of the discipline of statistical modelling.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2023-ADG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
9000 GENT
Belgium
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.