Causal diagram and Statistical analysis
Figure Causal diagram for the effect of time-varying treatment on cardiovascular or mortality outcome.This step generally stimulates randomized assignment of treatment at each visit within each stratum of previous covariate values. The two steps iteratively search for different coefficient values of causal variable Figure The process of adjustment in G-estimation. (The analysis also adjusted for loss to follow-up using inverse probability weighting of uncensored subjects. We also fitted conventional Weibull accelerated failure time (AFT) model using two modeling strategies: the first model adjusted for baseline confounders and the second model adjusted for both baseline and time-varying confounders. The results of AFT models were reported as hazard ratios with 95% confidence intervals (CIs) and the result of G-estimation was reported as hazard ratio with bootstrap-based 95% CI