Description
Mediation Analysis using Interventional Effects.
Description
Implementing the interventional effects for mediation analysis for up to 3 mediators. The methods used are based on VanderWeele, Vansteelandt and Robins (2014) <doi:10.1097/ede.0000000000000034>, Vansteelandt and Daniel (2017) <doi:10.1097/ede.0000000000000596> and Chan and Leung (2020; unpublished manuscript, available on request from the author of this package). Linear regression, logistic regression and Poisson regression are used for continuous, binary and count mediator/outcome variables respectively.
README.md
intmed
The intmed is for conducting mediation analysis using the interventional effect approach. It is built upon the work by VanderWeele, Vansteelandt and Robins (2014; https://dx.doi.org/10.1097/ede.0000000000000034) , Vansteelandt and Daniel (2017; https://dx.doi.org/10.1097/ede.0000000000000596) and Chan and Leung (2020; unpublished manuscript, available on request). The indirect effect mediated through a mediator M is defined as the average difference in the potential outcome in the population when there is an intervention that shifts the distribution of the mediator from what would have realised from unexposed to exposed, while holding the exposure level constant as exposed.