G-estimation
G-estimation estimates average treatment effects - in our case, average treatment effect differences between treatment groups - in potential outcomes in a structural nested mean model [In the structural nested mean model, following the notation of Hernán and Robins (2019), we model the expected conditional difference between the potential outcome under treatment For estimating this average treatment effect difference using G-estimation, we search for Compared to the Bayesian Network with time adjustment and the unadjusted Bayesian Network, we do not use lags in this model. Here, we used generalized estimating equations with 