Universal Difference-in-Differences for Causal Inference in Epidemiology.

ABSTRACT: Difference-in-differences is undoubtedly one of the most widely used methods for evaluating the causal effect of an intervention in observational (i.e., nonrandomized) settings. The approach is typically used when pre- and postexposure outcome measurements are available, and one can reasonably assume that the association of the unobserved confounder with the outcome has the same absolute magnitude in the two exposure arms and is constant over time; a so-called parallel trends assumption. The parallel trends assumption may not be credible in many practical settings, for example, if the outcome is binary, a count, or polytomous, as well as when an uncontrolled confounder exhibits nonadditive effects on the distribution of the outcome, even if such effects are constant over time. We introduce

SUBMITTER: Tchetgen Tchetgen EJ 

PROVIDER: S-EPMC10683972 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature