Multiply Robust Causal Inference with Double-Negative Control Adjustment for Categorical Unmeasured Confounding
分类未观测混杂下双重负控调整的多重稳健因果推断
Summary Unmeasured confounding is a threat to causal inference in observational studies. In recent years, the use of negative controls to mitigate unmeasured confounding has gained increasing recognition and popularity. Negative controls have a long-standing tradition in laboratory sciences and epidemiology to rule out non-causal explanations, although they have been used primarily for bias detection. Recently, Miao and colleagues have described sufficient conditions under…