4 papers
crumble: A comprehensive framework for modern causal mediation analysis with intermediate confounding
Richard Liu, Nicholas T. Williams, Kara E. Rudolph +1
Causal mediation analysis is widely used to investigate how causal effects operate through specific pathways linking treatments or exposures to outcomes. Recently, \texttt{crumble}…
Computationally and statistically efficient estimation of time-smoothed counterfactual curves
Herbert P. Susmann, Nicholas T. Williams, Richard Liu +2
Longitudinal causal inference is concerned with defining, identifying, and estimating the effect of a time-varying intervention on a time-varying outcome that is indexed by a follo…
General targeted machine learning for modern causal mediation analysis
Richard Liu, Nicholas T. Williams, Kara E. Rudolph +1
Causal mediation analyses investigate the mechanisms through which causes exert their effects, and are therefore central to scientific progress. The literature on the non-parametri…
Two-Step Targeted Minimum-Loss Based Estimation for Non-Negative Two-Part Outcomes
Nicholas T. Williams, Richard Liu, Katherine L. Hoffman +3
Non-negative two-part outcomes are defined as outcomes with a density function that have a zero point mass but are otherwise positive. Examples, such as healthcare expenditure and…