On the Validity of Covariate Adjustment for Estimating Causal Effects

15 March 2012

Papers citing "On the Validity of Covariate Adjustment for Estimating Causal Effects"

42 / 42 papers shown

Title
Identifiability by common backdoor in summary causal graphs of time series Clément Yvernes Charles K. Assaad Emilie Devijver Éric Gaussier CML 44 0 0 17 Jun 2025
Complete Characterization for Adjustment in Summary Causal Graphs of Time Series Clément Yvernes Emilie Devijver Éric Gaussier CML 36 1 0 17 Jun 2025
DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation Emre Kavak Tom Nuno Wolf Christian Wachinger CML 28 0 0 13 Jun 2025
Your Assumed DAG is Wrong and Here's How To Deal With It Kirtan Padh Zhufeng Li Cecilia Casolo Niki Kilbertus CML 111 0 0 24 Feb 2025
Practically Effective Adjustment Variable Selection in Causal Inference Atsushi Noda Takashi Isozaki 117 0 0 04 Feb 2025
Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables Zheng Li Feng Xie Xichen Guo Yan Zeng Hao Zhang Zhi Geng CML 225 0 0 25 Nov 2024
OCDB: Revisiting Causal Discovery with a Comprehensive Benchmark and Evaluation Framework Wei Zhou Hong Huang Guowen Zhang Ruize Shi Kehan Yin Yuanyuan Lin Bang Liu CML 82 1 0 07 Jun 2024
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals Y. Gat Nitay Calderon Amir Feder Alexander Chapanin Amit Sharma Roi Reichart 133 36 0 01 Oct 2023
Confounder selection via iterative graph expansion F. R. Guo Qingyuan Zhao CML 57 6 0 12 Sep 2023
A continuous Structural Intervention Distance to compare Causal Graphs Mihir Dhanakshirur F. Laumann Junhyung Park Mauricio Barahona CML 47 4 0 31 Jul 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 56 1 0 16 Jan 2023
Finding and Listing Front-door Adjustment Sets H. Jeong Jin Tian Elias Bareinboim 81 9 0 11 Oct 2022
Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey Debo Cheng Jiuyong Li Lin Liu Jixue Liu T. Le CML 94 32 0 20 Aug 2022
Graphical tools for selecting conditional instrumental sets Leonard Henckel Martin Buttenschon Marloes H. Maathuis CML 88 9 0 07 Aug 2022
Learning Counterfactually Invariant Predictors Francesco Quinzan Cecilia Casolo Krikamol Muandet Yucen Luo Niki Kilbertus 118 10 0 20 Jul 2022
On The Universality of Diagrams for Causal Inference and The Causal Reproducing Property Sridhar Mahadevan 72 5 0 06 Jul 2022
Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications Marcel Wienöbst Max Bannach Maciej Liskiewicz 61 10 0 05 May 2022
Orthogonal Statistical Learning with Self-Concordant Loss Lang Liu Carlos Cinelli Zaïd Harchaoui 53 2 0 30 Apr 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 100 46 0 01 Apr 2022
A note on efficient minimum cost adjustment sets in causal graphical models Ezequiel Smucler A. Rotnitzky CML 68 8 0 06 Jan 2022
Long Story Short: Omitted Variable Bias in Causal Machine Learning Victor Chernozhukov Carlos Cinelli Whitney Newey Amit Sharma Vasilis Syrgkanis CML 66 37 0 26 Dec 2021
Causal Markov Boundaries Sofia Triantafillou Fattaneh Jabbari Gregory F. Cooper CML OOD 55 5 0 12 Mar 2021
Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables Jakob Runge CML 94 27 0 20 Feb 2021
Sufficient Dimension Reduction for Average Causal Effect Estimation Debo Cheng Jiuyong Li Lin Liu Jixue Liu CML 51 15 0 14 Sep 2020
Efficient least squares for estimating total effects under linearity and causal sufficiency By F. Richard Guo Emilija Perković CML 109 13 0 08 Aug 2020
Efficient adjustment sets in causal graphical models with hidden variables Ezequiel Smucler F. Sapienza A. Rotnitzky CML OffRL 100 33 0 22 Apr 2020
Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables Rohit Bhattacharya Razieh Nabi I. Shpitser CML 108 64 0 27 Mar 2020
On efficient adjustment in causal graphs Jan-Jelle Witte Leonard Henckel Marloes H. Maathuis Vanessa Didelez CML 80 70 0 17 Feb 2020
Efficient adjustment sets for population average treatment effect estimation in non-parametric causal graphical models A. Rotnitzky Ezequiel Smucler CML 96 31 0 01 Dec 2019
Identifying causal effects in maximally oriented partially directed acyclic graphs Emilija Perković CML 69 39 0 07 Oct 2019
Graphical Criteria for Efficient Total Effect Estimation via Adjustment in Causal Linear Models Leonard Henckel Emilija Perković Marloes H. Maathuis CML 112 109 0 04 Jul 2019
Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias Patrick Forré Joris M. Mooij CML 89 32 0 02 Jan 2019
Separators and Adjustment Sets in Causal Graphs: Complete Criteria and an Algorithmic Framework Benito van der Zander Maciej Liskiewicz J. Textor CML 81 37 0 28 Feb 2018
Budgeted Experiment Design for Causal Structure Learning AmirEmad Ghassami Saber Salehkaleybar Negar Kiyavash Elias Bareinboim CML 116 64 0 11 Sep 2017
Interpreting and using CPDAGs with background knowledge Emilija Perković M. Kalisch Marloes H. Maathuis 83 52 0 07 Jul 2017
Evaluating Causal Models by Comparing Interventional Distributions Dan Garant David D. Jensen CML 143 12 0 16 Aug 2016
Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs Emilija Perković J. Textor M. Kalisch Marloes H. Maathuis OffRL 95 149 0 22 Jun 2016
A Complete Generalized Adjustment Criterion Emilija Perković J. Textor M. Kalisch Marloes H. Maathuis OffRL CML 85 73 0 06 Jul 2015
A generalized back-door criterion Marloes H. Maathuis Diego Colombo 122 36 0 22 Jul 2013
Structural Intervention Distance (SID) for Evaluating Causal Graphs J. Peters Peter Buhlmann CML 114 40 0 05 Jun 2013
Confounding Equivalence in Causal Inference Judea Pearl A. Paz CML 85 36 0 15 Mar 2012
Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective J. Textor Maciej Liskiewicz CML 85 70 0 14 Feb 2012