Research Explorer

Project

Honest data-adaptive inference for treatment effects
Code
01J02217
Duration
01 October 2017 → 30 September 2021
Funding
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Applied mathematics in specific fields
    • Statistics
    • Numerical methods
Keywords
Causal inference High-dimensional data analysis Post-regularisation inference
 
Project description
 

The estimation of treatment effects in observational studies is susceptible to bias due to model misspecification. Corresponding confidence intervals and p-values are moreover overly optimistic when variable selection or regularisation techniques are adopted. We will therefore develop treatment effect estimators which are less sensitive to model specification, along with honest confidence intervals and hypothesis tests.