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We should implement a procedure that estimates the full data parameter in the presence of a censoring process, e.g., a data structure like O = (W, A, Z, C, CY), for censoring indicator C. Such an approach would be based on the joint intervention setting C = 1 and the joint intervention on {A, Z} that defines our causal parameters. The estimation procedures would then simply incorporate an extra set of IP weights, specifically to address this intervention, i.e., 1/g(C = 1 | …).
The text was updated successfully, but these errors were encountered:
We should implement a procedure that estimates the full data parameter in the presence of a censoring process, e.g., a data structure like O = (W, A, Z, C, CY), for censoring indicator C. Such an approach would be based on the joint intervention setting C = 1 and the joint intervention on {A, Z} that defines our causal parameters. The estimation procedures would then simply incorporate an extra set of IP weights, specifically to address this intervention, i.e., 1/g(C = 1 | …).
The text was updated successfully, but these errors were encountered: