Journal of Causal Inference

2013 - 2025

Current editor(s): Elias Bareinboim, Jin Tian and Iván Díaz

From De Gruyter
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Balancing Score Adjusted Targeted Minimum Loss-based Estimation pp. 139-155: Lendle Samuel David, Fireman Bruce and J. van der Laan Mark
Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition pp. 157-175: Gilbert Peter B., Gabriel Erin E., Huang Ying and Chan Ivan S.F.
A Causal Perspective on OSIM2 Data Generation, with Implications for Simulation Study Design and Interpretation pp. 177-187: Gruber Susan
Parameter Identifiability of Discrete Bayesian Networks with Hidden Variables pp. 189-205: Allman Elizabeth S., Rhodes John A., Elena Stanghellini and Valtorta Marco
The Bayesian Causal Effect Estimation Algorithm pp. 207-236: Talbot Denis, Lefebvre Geneviève and Atherton Juli
Propensity Score Analysis with Survey Weighted Data pp. 237-249: Ridgeway Greg, Kovalchik Stephanie Ann, Griffin Beth Ann and Kabeto Mohammed U.
Reply to Professor Pearl’s Comment pp. 251-252: Ding Peng and Miratrix Luke W.
M-bias, Butterfly Bias, and Butterfly Bias with Correlated Causes – A Comment on Ding and Miratrix (2015) pp. 253-258: Thoemmes Felix
Generalizing Experimental Findings pp. 259-266: Pearl Judea

Randomization Inference in the Regression Discontinuity Design: An Application to Party Advantages in the U.S. Senate pp. 1-24: Matias Cattaneo, Frandsen Brigham R. and Titiunik Rocío
A Boosting Algorithm for Estimating Generalized Propensity Scores with Continuous Treatments pp. 25-40: Zhu Yeying, Coffman Donna L. and Ghosh Debashis
To Adjust or Not to Adjust? Sensitivity Analysis of M-Bias and Butterfly-Bias pp. 41-57: Ding Peng and Miratrix Luke W.
Comment on Ding and Miratrix: “To Adjust or Not to Adjust?” pp. 59-60: Pearl Judea
Targeted Learning of the Mean Outcome under an Optimal Dynamic Treatment Rule pp. 61-95: J. van der Laan Mark and Luedtke Alexander R.
On the Intersection Property of Conditional Independence and its Application to Causal Discovery pp. 97-108: Peters Jonas
Assumption Trade-Offs When Choosing Identification Strategies for Pre-Post Treatment Effect Estimation: An Illustration of a Community-Based Intervention in Madagascar pp. 109-130: Weber Ann M., J. van der Laan Mark and Petersen Maya L.
Conditioning on Post-treatment Variables pp. 131-137: Pearl Judea

The Deductive Approach to Causal Inference pp. 115-129: Pearl Judea
Reducing Bias Amplification in the Presence of Unmeasured Confounding through Out-of-Sample Estimation Strategies for the Disease Risk Score pp. 131-146: Wyss Richard, Lunt Mark, Brookhart M. Alan, Glynn Robert J. and Stürmer Til
Targeted Maximum Likelihood Estimation for Dynamic and Static Longitudinal Marginal Structural Working Models pp. 147-185: Petersen Maya, Schwab Joshua, Gruber Susan, Blaser Nello, Schomaker Michael and Mark van der Laan
Testing for the Unconfoundedness Assumption Using an Instrumental Assumption pp. 187-199: Xavier de Luna and Per Johansson
Causality, a Trialogue pp. 201-241: Chambaz Antoine, Drouet Isabelle and Thalabard Jean-Christophe
Graphoids over Counterfactuals pp. 243-248: Pearl Judea
Erratum to Is Scientific Knowledge Useful for Policy Analysis? A Peculiar Theorem Says: No [J Causal Inference DOI: 10.1515/jci-2014-0017] pp. 249-249: Pearl Judea

Monotone Confounding, Monotone Treatment Selection and Monotone Treatment Response pp. 1-12: Jiang Zhichao, Chiba Yasutaka and VanderWeele Tyler J.
Causal Inference for a Population of Causally Connected Units pp. 13-74: J. van der Laan Mark
Confounding Equivalence in Causal Inference pp. 75-93: Pearl Judea and Paz Azaria
Semiparametric Estimation of the Impacts of Longitudinal Interventions on Adolescent Obesity using Targeted Maximum-Likelihood: Accessible Estimation with the ltmle Package pp. 95-108: Decker Anna L., Hubbard Alan, Crespi Catherine M., Seto Edmund Y.W. and Wang May C.
Is Scientific Knowledge Useful for Policy Analysis? A Peculiar Theorem Says: No pp. 109-112: Pearl Judea
Erratum to Revisiting a Discrepant Result: A Propensity Score Analysis, the Paired Availability Design for Historical Controls, and a Meta-Analysis of Randomized Trials [J Causal Inference DOI: 10.1515/jci-2013-0005] pp. 113-113: Baker Stuart G. and Lindeman Karen S.

Targeted Data Adaptive Estimation of the Causal Dose–Response Curve pp. 171-192: Díaz Iván and J. van der Laan Mark
Analysis of Subgroup Data of Clinical Trials pp. 193-207: Tsai Kao-Tai and Peace Karl
Robust Inferences from a Before-and-After Study with Multiple Unaffected Control Groups pp. 209-234: Wang Pengyuan, Traskin Mikhail and Small Dylan S.
Targeted Minimum Loss-Based Estimation of Causal Effects in Right-Censored Survival Data with Time-Dependent Covariates: Warfarin, Stroke, and Death in Atrial Fibrillation pp. 235-254: Brooks Jordan C., J. van der Laan Mark, Singer Daniel E. and Go Alan S.
The Curse of Free-Will and the Paradox of Inevitable Regret pp. 255-257: Pearl Judea

Causal inference under multiple versions of treatment pp. 1-20: VanderWeele Tyler J. and Hernan Miguel A.
A Marginal Structural Modeling Approach with Super Learning for a Study on Oral Bisphosphonate Therapy and Atrial Fibrillation pp. 21-50: Neugebauer Romain, Chandra Malini, Paredes Antonio, J. Graham David, McCloskey Carolyn and S. Go Alan
Revisiting a Discrepant Result: A Propensity Score Analysis, the Paired Availability Design for Historical Controls, and a Meta-Analysis of Randomized Trials pp. 51-82: G. Baker Stuart and S. Lindeman Karen
Estimating the Effect of a Community-Based Intervention with Two Communities pp. 83-106: J. van der Laan Mark, Petersen Maya and Zheng Wenjing
A General Algorithm for Deciding Transportability of Experimental Results pp. 107-134: Bareinboim Elias and Pearl Judea
A Class of Unbiased Estimators of the Average Treatment Effect in Randomized Experiments pp. 135-154: Aronow Peter M. and Middleton Joel A.
Linear Models: A Useful “Microscope” for Causal Analysis pp. 155-170: Pearl Judea