Appendix B — Appendix: Additional topics of interest

The literature on mediation analysis has grown considerably in the last few decades and there are now many novel methods to tackle important questions with complex data structures. While we are unable to cover all these interesting methods in this workshop, here we provide a few references for further reading.

This list is not meant to be comprehensive, just some of our own work and some work by others that we know and consider interesting.

B.1 Mediation with multiple mediators and multiple intermediate confounders

Note that the medoutcon R package works for multiple mediators but is limited to settings with only a single, binary intermediate confounder. If your data scenario includes multiple mediators and multiple intermediate confounders, you should consider using the HDmediation R package instead.

• Practical causal mediation analysis: extending nonparametric estimators to estimate the mediated effects of housing voucher receipt on adolescent risk behavior By Kara E. Rudolph, Nicholas Williams, and Iván Díaz

B.2 Mediation with monotonicity of A-Z relationship

• On identification of natural direct effects when a confounder of the mediator is directly affected by exposure by Eric J. Tchetgen Tchetgen and Tyler J. VanderWeele
• Efficient and flexible estimation of natural mediation effects under intermediate confounding and monotonicity constraints by Kara E. Rudolph and Iván Díaz

B.3 Mediation with instrumental variables

• Direct and indirect treatment effects–causal chains and mediation analysis with instrumental variables by Markus Frolich and Martin Huber
• Causal mediation with instrumental variables by Kara E. Rudolph, Nicholas Williams, and Iván Díaz

B.4 Mediation with separable effects

• An Interventionist Approach to Mediation Analysis by James M. Robins, Thomas S. Richardson, and Ilya Shpitser
• Conditional Separable Effects by Mats J. Stensrud, James M. Robins, Aaron Sarvet, Eric J. Tchetgen Tchetgen, and Jessica G. Young
• Separable Effects for Causal Inference in the Presence of Competing Events by Mats J. Stensrud, Jessica G. Young, Vanessa Didelez, James M. Robins, and Miguel A. Hernán
• A Generalized Theory of Separable Effects in Competing Event Settings by Mats J. Stensrud, Miguel A. Hernán, Eric J. Tchetgen Tchetgen, James M. Robins, Vanessa Didelez, and Jessica G. Young