Figure 1.

Methods to control for confounding in observational studies.*Multiple imputation is valid when the assumption of Missing at Random (MAR) holds;**if time-varying confounder is affected by previous treatment, all PS-based methods except marginal structural model (MSM) using inverse probability of treatment weight (IPTW) will give biased estimate;***self-controlled case-series design; ♠)stratification using effect modifier and adjustment within the strata to account for other covariates; ♠♠)Disease risk score (prognostic score) method; ♠♠♠)restriction or choosing an active comparison group vs non-user group; ♣)G-formula and ♣♣)G-estimation of structural nested models, which rely on specification of the outcome model; ♣♣♣)instrumental variable methods. (Adapted in part from Schneeweiss (2006), Uddin et al. (2016), and Zhang et al. (2018)).