Robust CATE estimation using novel ensemble methods.

Oshri Machluf¹, Tzviel Frostig¹, Tomer Milo¹, Bradley P Carlin¹, Elad Berkman¹, Raviv Pryluk¹

¹Research Department, PhaseV Trials, Inc., Cambridge, MA, USA.

Abstract

The estimation of Conditional Average Treatment Effects (CATE) is crucial for understanding the heterogeneity of treatment effects in clinical trials. We evaluate the performance of common methods, including causal forests and various meta-learners, across a diverse set of scenarios, revealing that each of the methods struggles in one or more of the tested scenarios. Given the inherent uncertainty…

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