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Heterogeneous causal effects with imperfect compliance: a Bayesian
  machine learning approach

Heterogeneous causal effects with imperfect compliance: a Bayesian machine learning approach

29 May 2019
Falco J. Bargagli-Stoffi
Kristof De-Witte
G. Gnecco
ArXivPDFHTML

Papers citing "Heterogeneous causal effects with imperfect compliance: a Bayesian machine learning approach"

3 / 3 papers shown
Title
Conditional Front-door Adjustment for Heterogeneous Treatment Assignment Effect Estimation Under Non-adherence
Conditional Front-door Adjustment for Heterogeneous Treatment Assignment Effect Estimation Under Non-adherence
Winston Chen
Trenton Chang
Jenna Wiens
CML
50
0
0
08 May 2025
A flexible Bayesian g-formula for causal survival analyses with time-dependent confounding
A flexible Bayesian g-formula for causal survival analyses with time-dependent confounding
Xinyuan Chen
Liangyuan Hu
Fan Li
CML
28
0
0
04 Feb 2024
Estimating individual treatment effects under unobserved confounding
  using binary instruments
Estimating individual treatment effects under unobserved confounding using binary instruments
Dennis Frauen
Stefan Feuerriegel
CML
26
18
0
17 Aug 2022
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