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.
Semiparametric estimation of structural nested mean models with irregularly spaced longitudinal observations.Biometrics, 78(3):937–949, April 2021
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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.