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Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective

Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective

14 February 2012
J. Textor
Maciej Liskiewicz
    CML
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Papers citing "Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective"

3 / 3 papers shown
Title
Practically Effective Adjustment Variable Selection in Causal Inference
Practically Effective Adjustment Variable Selection in Causal Inference
Atsushi Noda
Takashi Isozaki
66
0
0
04 Feb 2025
Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables
Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables
Zheng Li
Feng Xie
Yan Zeng
Zhi Geng
Hao Zhang
Zhi Geng
CML
79
0
0
25 Nov 2024
Separators and Adjustment Sets in Causal Graphs: Complete Criteria and
  an Algorithmic Framework
Separators and Adjustment Sets in Causal Graphs: Complete Criteria and an Algorithmic Framework
Benito van der Zander
Maciej Liskiewicz
J. Textor
CML
19
34
0
28 Feb 2018
1