This work establishes identification conditions and marginal g-formulas for causal effects under dynamic treatment regimes in marked point process data by adapting discrete-time causal assumptions via martingale theory.
a new approach to causal inference in mor- tality studies with a sustained exposure period—application to control of the healthy worker survivor effect
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On causal inference with marked point process data
This work establishes identification conditions and marginal g-formulas for causal effects under dynamic treatment regimes in marked point process data by adapting discrete-time causal assumptions via martingale theory.