Journal of Causal Inference

2013 - 2025

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

From De Gruyter
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Volume 9, issue 1, 2021

Two seemingly paradoxical results in linear models: the variance inflation factor and the analysis of covariance pp. 1-8

Ding Peng

Identification of causal intervention effects under contagion pp. 9-38

Cai Xiaoxuan, Loh Wen Wei and Crawford Forrest W.

Decision-theoretic foundations for statistical causality pp. 39-77

Dawid Philip

Radical empiricism and machine learning research pp. 78-82

Pearl Judea

A fundamental measure of treatment effect heterogeneity pp. 83-108

Levy Jonathan, Mark van der Laan, Hubbard Alan and Pirracchio Romain

Estimating the effect of central bank independence on inflation using longitudinal targeted maximum likelihood estimation pp. 109-146

Baumann Philipp F. M., Schomaker Michael and Enzo Rossi

Designing experiments informed by observational studies pp. 147-171

Rosenman Evan T. R. and Owen Art B.

Nonparametric inference for interventional effects with multiple mediators pp. 172-189

Benkeser David and Ran Jialu

Novel bounds for causal effects based on sensitivity parameters on the risk difference scale pp. 190-210

Sjölander Arvid and Hössjer Ola

Estimating causal effects with the neural autoregressive density estimator pp. 211-228

Garrido Sergio, Borysov Stanislav, Rich Jeppe and Pereira Francisco

On the bias of adjusting for a non-differentially mismeasured discrete confounder pp. 229-249

Peña Jose M., Balgi Sourabh, Sjölander Arvid and Gabriel Erin E.

Learning linear non-Gaussian graphical models with multidirected edges pp. 250-263

Liu Yiheng, Robeva Elina and Wang Huanqing

Conditional as-if analyses in randomized experiments pp. 264-284

Pashley Nicole E., Basse Guillaume W. and Miratrix Luke W.

Causal versions of maximum entropy and principle of insufficient reason pp. 285-301

Janzing Dominik

Incremental intervention effects in studies with dropout and many timepoints# pp. 302-344

Kim Kwangho, Kennedy Edward H. and Naimi Ashley I.

Optimal balancing of time-dependent confounders for marginal structural models pp. 345-369

Kallus Nathan and Santacatterina Michele

Volume 8, issue 1, 2020

Unifying Gaussian LWF and AMP Chain Graphs to Model Interference pp. 1-21

Peña Jose M.

Unifying Gaussian LWF and AMP Chain Graphs to Model Interference pp. 1-21

Peña Jose M.

A Combinatorial Solution to Causal Compatibility pp. 22-53

Fraser Thomas C.

A Combinatorial Solution to Causal Compatibility pp. 22-53

Fraser Thomas C.

Post-randomization Biomarker Effect Modification Analysis in an HIV Vaccine Clinical Trial pp. 54-69

Gilbert Peter B., Blette Bryan S., Shepherd Bryan E. and Hudgens Michael G.

Post-randomization Biomarker Effect Modification Analysis in an HIV Vaccine Clinical Trial pp. 54-69

Gilbert Peter B., Blette Bryan S., Hudgens Michael G. and Shepherd Bryan E.

The Inflation Technique Completely Solves the Causal Compatibility Problem pp. 70-91

Navascués Miguel and Wolfe Elie

The Inflation Technique Completely Solves the Causal Compatibility Problem pp. 70-91

Navascués Miguel and Wolfe Elie

Averaging causal estimators in high dimensions pp. 92-107

Antonelli Joseph and Cefalu Matthew

Estimating population average treatment effects from experiments with noncompliance pp. 108-130

Ottoboni Kellie N. and Poulos Jason V.

A Two-Stage Joint Modeling Method for Causal Mediation Analysis in the Presence of Treatment Noncompliance pp. 131-149

Park Soojin and Kürüm Esra

On the Monotonicity of a Nondifferentially Mismeasured Binary Confounder pp. 150-163

Peña Jose M.

Beyond Manipulation: Administrative Sorting in Regression Discontinuity Designs pp. 164-181

Crespo Cristian

Instruments with Heterogeneous Effects: Bias, Monotonicity, and Localness pp. 182-208

Nick Huntington-Klein

When is a Match Sufficient? A Score-based Balance Metric for the Synthetic Control Method pp. 209-228

Parast Layla, Hunt Priscillia, Griffin Beth Ann and David Powell

A note on a sensitivity analysis for unmeasured confounding, and the related E-value pp. 229-248

Sjölander Arvid

Estimating Average Treatment Effects Utilizing Fractional Imputation when Confounders are Subject to Missingness pp. 249-271

Corder Nathan and Yang Shu

Identification and Estimation of Intensive Margin Effects by Difference-in-Difference Methods pp. 272-285

Markus Hersche and Elias Moor

Direct Effects under Differential Misclassification in Outcomes, Exposures, and Mediators pp. 286-299

Li Yige and VanderWeele Tyler J.

Improved Doubly Robust Estimation in Marginal Mean Models for Dynamic Regimes pp. 300-314

Sun Hao, Ertefaie Ashkan, Lu Xin and Johnson Brent A.

Volume 7, issue 2, 2019

Sufficient Causes: On Oxygen, Matches, and Fires pp. 8

Pearl Judea

Technical Considerations in the Use of the E-Value pp. 11

VanderWeele Tyler J., Ding Peng and Mathur Maya

A Gaussian Process Framework for Overlap and Causal Effect Estimation with High-Dimensional Covariates pp. 13

Ghosh Debashis and Cruz Cortés Efrén

Regression Adjustments for Estimating the Global Treatment Effect in Experiments with Interference pp. 36

Chin Alex

The Inflation Technique for Causal Inference with Latent Variables pp. 51

Wolfe Elie, Spekkens Robert W. and Fritz Tobias

The Inflation Technique for Causal Inference with Latent Variables pp. 51

Wolfe Elie, Spekkens Robert W. and Fritz Tobias

Volume 7, issue 1, 2019

A Falsifiability Characterization of Double Robustness Through Logical Operators pp. 4

Frangakis Constantine

On the Interpretation of do(x)do(x) pp. 6

Pearl Judea

Estimating Causal Effects of New Treatments Despite Self-Selection: The Case of Experimental Medical Treatments pp. 8

Hazlett Chad

Learning Heterogeneity in Causal Inference Using Sufficient Dimension Reduction pp. 14

Luo Wei, Wu Wenbo and Zhu Yeying

Estimating Mann–Whitney-Type Causal Effects for Right-Censored Survival Outcomes pp. 15

Zhang Zhiwei, Liu Chunling, Ma Shujie and Zhang Min

The Entry of Randomized Assignment into the Social Sciences pp. 16

Jamison Julian C.

New Traffic Conflict Measure Based on a Potential Outcome Model pp. 19

Yamada Kentaro and Kuroki Manabu

Approximate Kernel-Based Conditional Independence Tests for Fast Non-Parametric Causal Discovery pp. 24

Strobl Eric V., Zhang Kun and Visweswaran Shyam

Randomization Tests that Condition on Non-Categorical Covariate Balance pp. 29

Branson Zach and Miratrix Luke W.