Journal of Causal Inference

2013 - 2025

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

From De Gruyter
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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