ainaimi/trimediation: Controlled Direct Effect Calculation

Social epidemiologists often seek to determine the mechanisms that underlie health disparities. This work is typically based on mediation procedures that may not be justified with exposures of common interest in social epidemiology. This tool allows us to explore the consequences of using standard approaches, referred to as the difference and generalized product methods, when mediator-outcome confounders are associated with the exposure. Available models are: 1) The inverse probability-weighted marginal structural models, 2) The structural transformation method, 3) The doubly robust g-estimation of a structural nested model, and 4) The doubly robust targeted minimum loss-based estimation. This allows the user to explore ways in which a Standard approach for mediation analysis can yield misleading results. Also implemented are non-parametric boostrapping methods for confidence interval evaluation. For more information, please see: Naimi, A. I., Schnitzer, M. E., Moodie, E. E. M., & Bodnar, L. M. (2016). Mediation Analysis for Health Disparities Research. American Journal of Epidemiology, 184(4), 315–324. https://doi.org/10.1093/aje/kwv329

Getting started

Package details

AuthorAshley Naimi
MaintainerAshley Naimi <ashley.naimi@pitt.edu>
LicenseGPL-3
Version0.1.2
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("ainaimi/trimediation")
ainaimi/trimediation documentation built on May 25, 2019, 2:24 p.m.