activity
20182022
collaborators

6 papers

stat.ME2022

Efficient and flexible estimation of natural mediation effects under intermediate confounding and monotonicity constraints

Kara E. Rudolph, Ivan Diaz

Natural direct and indirect effects are mediational estimands that decompose the average treatment effect and describe how outcomes would be affected by contrasting levels of a tre…

stat.AP2021

When the ends don't justify the means: Learning a treatment strategy to prevent harmful indirect effects

Kara E. Rudolph, Ivan Diaz

There is a growing literature on finding so-called optimal treatment rules, which are rules by which to assign treatment to individuals based on an individual's characteristics, su…

stat.ME2020

Efficiently transporting causal (in)direct effects to new populations under intermediate confounding and with multiple mediators

Kara E. Rudolph, Ivan Diaz

The same intervention can produce different effects in different sites. Transport mediation estimators can estimate the extent to which such differences can be explained by differe…

stat.ME2019

Non-parametric efficient causal mediation with intermediate confounders

Iván Díaz, Nima S. Hejazi, Kara E. Rudolph +1

Interventional effects for mediation analysis were proposed as a solution to the lack of identifiability of natural (in)direct effects in the presence of a mediator-outcome confoun…

stat.ME2019

Transporting stochastic direct and indirect effects to new populations

Kara E Rudolph, Jonathan Levy, Mark J van der Laan

Transported mediation effects may contribute to understanding how and why interventions may work differently when applied to new populations. However, we are not aware of any estim…

stat.ME2018

Complier stochastic direct effects: identification and robust estimation

Kara E Rudolph, Oleg Sofrygin, Mark J van der Laan

Mediation analysis is critical to understanding the mechanisms underlying exposure-outcome relationships. In this paper, we identify the instrumental variable (IV)-direct effect of…