A Note on G-Estimation of Causal Risk Ratios

AbstractG-estimation is a flexible, semiparametric approach for estimating exposure effects in epidemiologic studies. It has several underappreciated advantages over other propensity score –based methods popular in epidemiology, which we review in this article. However, it is rarely used in practice, due to a lack of off-the-shelf software. To rectify this, we show a simple trick for obtaining G-estimators of causal risk ratios using existing generalized estimating equations softwar e. We extend the procedure to more complex settings with time-varying confounders.

Source: American Journal of Epidemiology - March 12, 2018 Category: Epidemiology Source Type: research