Distribution-free mediation analysis for nonlinear models with confounding.

ABSTRACT: Recently, researchers have used a potential-outcome framework to estimate causally interpretable direct and indirect effects of an intervention or exposure on an outcome. One approach to causal-mediation analysis uses the so-called mediation formula to estimate the natural direct and indirect effects. This approach generalizes the classical mediation estimators and allows for arbitrary distributions for the outcome variable and mediator. A limitation of the standard (parametric) mediation formula approach is that it requires a specified mediator regression model and distribution; such a model may be difficult to construct and may not be of primary interest. To address this limitation, we propose a new method for causal-mediation analysis that uses the empirical distribution function, there

SUBMITTER: Albert JM 

PROVIDER: S-EPMC3773310 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature