Towards more plausible point-identifying assumptions in two-sample Mendelian randomization
Two-sample Mendelian randomization methods are reinterpreted as estimators of average causal effects under weaker identification assumptions than previously thought. The authors derive conditions, like Non Simultaneous Heterogeneity (NOSH), that imply summary-level homogeneity, clarifying the point-identifying assumptions required for these methods and improving their practical interpretation.