1 citations · 1 across the 3 of their papers we have counts for
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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…
Recanting twins: addressing intermediate confounding in mediation analysis
Tat-Thang Vo, Nicholas Williams, Richard Liu +2
The presence of intermediate confounders, also called recanting witnesses, is a fundamental challenge to the investigation of causal mechanisms in mediation analysis, preventing th…
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…
Leveraging Neural Networks to Profile Health Care Providers with Application to Medicare Claims
Wenbo Wu, Fan Li, Richard Liu +5
Encompassing numerous nationwide, statewide, and institutional initiatives in the United States, provider profiling has evolved into a major health care undertaking with ubiquitous…