mediationsens: Simulation-Based Sensitivity Analysis for Causal Mediation Studies

Simulation-based sensitivity analysis for causal mediation studies. It numerically and graphically evaluates the sensitivity of causal mediation analysis results to the presence of unmeasured pretreatment confounding. The proposed method has primary advantages over existing methods. First, using an unmeasured pretreatment confounder conditional associations with the treatment, mediator, and outcome as sensitivity parameters, the method enables users to intuitively assess sensitivity in reference to prior knowledge about the strength of a potential unmeasured pretreatment confounder. Second, the method accurately reflects the influence of unmeasured pretreatment confounding on the efficiency of estimation of the causal effects. Third, the method can be implemented in different causal mediation analysis approaches, including regression-based, simulation-based, and propensity score-based methods. It is applicable to both randomized experiments and observational studies.

Getting started

Package details

AuthorXu Qin and Fan Yang
MaintainerXu Qin <xuqin@pitt.edu>
LicenseGPL-2
Version0.0.2
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("mediationsens")

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mediationsens documentation built on July 2, 2020, 4:13 a.m.