Guido Biele

Causal Inference amid Missingness-Specific Independences and Mechanism Shifts

The recovery of causal effects in structural models with missing data often relies on $m$-graphs, which assume that missingness mechanisms do not directly influence substantive variables. Yet, in many real-world settings, missing data can alter decision-making processes, as the absence of key inform