A classical regression framework for mediation analysis: fitting one model to estimate mediation effects.

ABSTRACT: Mediation analysis explores the degree to which an exposure's effect on an outcome is diverted through a mediating variable. We describe a classical regression framework for conducting mediation analyses in which estimates of causal mediation effects and their variance are obtained from the fit of a single regression model. The vector of changes in exposure pathway coefficients, which we named the essential mediation components (EMCs), is used to estimate standard causal mediation effects. Because these effects are often simple functions of the EMCs, an analytical expression for their model-based variance follows directly. Given this formula, it is instructive to revisit the performance of routinely used variance approximations (e.g., delta method and resampling methods). Requiring the fit

SUBMITTER: Saunders CT 

PROVIDER: S-EPMC6180946 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature