Estimation and Validation of Ratio-based Conditional Average Treatment Effects Using Observational Data

15 Dec 2019Steve YadlowskyFabio PellegriniFederica LionettoStefan BrauneLu Tian

While sample sizes in randomized clinical trials are large enough to estimate the average treatment effect well, they are often insufficient for estimation of treatment-covariate interactions critical to studying data-driven precision medicine. Observational data from real world practice may play an important role in alleviating this problem... (read more)

PDF Abstract


No code implementations yet. Submit your code now


Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.