Orthogonal machine learning for conditional odds and risk ratios

ArXi:2604.10412v1 Announce Type: cross Conditional effects are commonly used measures for understanding how treatment effects vary across different groups, and are often used to target treatments/interventions to groups who benefit most. In this work we review existing methods and propose novel ones, focusing on the odds ratio (OR) and the risk ratio (RR