Figure 1. Approaches to Causal Inference.

A, The standard approach to causal inference between an exposure (or risk factor) and outcome using multiple regression. Such methods can only include measured confounders. However, the impact of unmeasured confounders can bias upward the estimate of the causal relationship between the exposure and the outcome. B, A co-relative approach to causal inference between an exposure (or risk factor) and outcome. This method controls for all familial confounders whether measured or unmeasured. However, the impact of nonfamilial confounders can bias upward the estimate of the causal relationship between the exposure and the outcome.