Journal of Causal Inference

2013 - 2025

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

From De Gruyter
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Volume 13, issue 1, 2025

Role of placebo samples in observational studies pp. 12

Ye Ting, He Qijia, Chen Shuxiao and Zhang Bo

Conservative inference for counterfactuals pp. 17

Balakrishnan Sivaraman, Kennedy Edward and Wasserman Larry

Optimal precision of coarse structural nested mean models to estimate the effect of initiating ART in early and acute HIV infection pp. 23

Lok Judith J.

Combining observational and experimental data for causal inference considering data privacy pp. 23

Mann Charlotte Z., Sales Adam C. and Gagnon-Bartsch Johann A.

The necessity of construct and external validity for deductive causal inference pp. 25

Esterling Kevin M., Brady David and Schwitzgebel Eric

Recovery and inference of causal effects with sequential adjustment for confounding and attrition pp. 29

Johan de Aguas, Pensar Johan, Varnet Pérez Tomás and Biele Guido

Targeting mediating mechanisms of social disparities with an interventional effects framework, applied to the gender pay gap in Western Germany pp. 30

Didden Christiane

Treatment effect estimation with observational network data using machine learning pp. 36

Emmenegger Corinne, Spohn Meta-Lina, Elmer Timon and Bühlmann Peter

Targeted maximum likelihood based estimation for longitudinal mediation analysis pp. 39

Wang Zeyi, Laan Lars van der, Petersen Maya, Gerds Thomas, Kvist Kajsa and Laan Mark van der

Causal structure learning in directed, possibly cyclic, graphical models pp. 41

Semnani Pardis and Robeva Elina

Decision making, symmetry and structure: Justifying causal interventions pp. 47

Johnston David O., Ong Cheng Soon and Williamson Robert C.

Volume 12, issue 1, 2024

Comparison of open-source software for producing directed acyclic graphs pp. 10

Pitts Amy J. and Fowler Charlotte R.

Sharp bounds for causal effects based on Ding and VanderWeele's sensitivity parameters pp. 10

Sjölander Arvid

Potential outcomes and decision-theoretic foundations for statistical causality: Response to Richardson and Robins pp. 11

Dawid Philip

From urn models to box models: Making Neyman's (1923) insights accessible pp. 12

Lin Winston, Dudoit Sandrine, Nolan Deborah and Speed Terence P.

Prospective and retrospective causal inferences based on the potential outcome framework pp. 15

Geng Zhi, Zhang Chao, Wang Xueli, Liu Chunchen and Wei Shaojie

Estimation of network treatment effects with non-ignorable missing confounders pp. 16

Sun Zhaohan, Zhu Yeying and Dubin Joel A.

Direct, indirect, and interaction effects based on principal stratification with a binary mediator pp. 16

Myoung-jae Lee

Optimal allocation of sample size for randomization-based inference from 2K factorial designs pp. 18

Ravichandran Arun, Pashley Nicole E., Libgober Brian and Dasgupta Tirthankar

Design-based RCT estimators and central limit theorems for baseline subgroup and related analyses pp. 18

Schochet Peter Z.

Mediation analyses for the effect of antibodies in vaccination pp. 19

Fay Michael P. and Follmann Dean A.

Causal inference with textual data: A quasi-experimental design assessing the association between author metadata and acceptance among ICLR submissions from 2017 to 2022 pp. 20

Chen Chang, Zhang Jiayao, Ye Ting, Roth Dan and Zhang Bo

Quantifying the quality of configurational causal models pp. 20

Baumgartner Michael and Falk Christoph

Neyman meets causal machine learning: Experimental evaluation of individualized treatment rules pp. 20

Li Michael Lingzhi and Imai Kosuke

Detecting treatment interference under K-nearest-neighbors interference pp. 20

Alzubaidi Samirah H. and Higgins Michael J.

Regression(s) discontinuity: Using bootstrap aggregation to yield estimates of RD treatment effects pp. 21

Mark Long and Rooklyn Jordan

Current philosophical perspectives on drug approval in the real world pp. 21

Landes Jürgen and Auker-Howlett Daniel J.

Energy balancing of covariate distributions pp. 22

Huling Jared D. and Mak Simon

Conditional generative adversarial networks for individualized causal mediation analysis pp. 23

Huan Cheng, Sun Rongqian and Song Xinyuan

Improved sensitivity bounds for mediation under unmeasured mediator–outcome confounding pp. 24

Sjölander Arvid and Waernbaum Ingeborg

Evaluating Boolean relationships in Configurational Comparative Methods pp. 25

Luna De Souter

Doubly weighted M-estimation for nonrandom assignment and missing outcomes pp. 25

Negi Akanksha

An optimal transport approach to estimating causal effects via nonlinear difference-in-differences pp. 26

Torous William, Gunsilius Florian and Rigollet Philippe

Double machine learning and design in batch adaptive experiments pp. 27

Li Harrison H. and Owen Art B.

A phenomenological account for causality in terms of elementary actions pp. 28

Janzing Dominik and Mejia Sergio Hernan Garrido

An approach to nonparametric inference on the causal dose–response function pp. 28

Hudson Aaron, Geng Elvin H., Odeny Thomas A., Bukusi Elizabeth A., Petersen Maya L. and J. van der Laan Mark

Some theoretical foundations for the design and analysis of randomized experiments pp. 30

Shi Lei and Li Xinran

The functional average treatment effect pp. 30

Sparkes Shane, Garcia Erika and Zhang Lu

Foundations of causal discovery on groups of variables pp. 32

Wahl Jonas, Ninad Urmi and Runge Jakob

Bias formulas for violations of proximal identification assumptions in a linear structural equation model pp. 34

Cobzaru Raluca, Welsch Roy, Finkelstein Stan, Ng Kenney and Shahn Zach

Nonparametric estimation of conditional incremental effects pp. 42

McClean Alec, Branson Zach and Kennedy Edward H.

Interactive identification of individuals with positive treatment effect while controlling false discoveries pp. 43

Duan Boyan, Wasserman Larry and Ramdas Aaditya

Volume 11, issue 1, 2023

On the pitfalls of Gaussian likelihood scoring for causal discovery pp. 11

Schultheiss Christoph and Bühlmann Peter

Double machine learning and automated confounder selection: A cautionary tale pp. 12

Paul Hünermund, Louw Beyers and Itamar Caspi

Personalized decision making – A conceptual introduction pp. 13

Mueller Scott and Pearl Judea

Testing for treatment effect twice using internal and external controls in clinical trials pp. 13

Yi Yanyao, Zhang Ying, Du Yu and Ye Ting

Identification of in-sample positivity violations using regression trees: The PoRT algorithm pp. 13

Danelian Gabriel, Foucher Yohann, Léger Maxime, Le Borgne Florent and Chatton Arthur

On the dimensional indeterminacy of one-wave factor analysis under causal effects pp. 15

VanderWeele Tyler J. and Batty Charles J. K.

All models are wrong, but which are useful? Comparing parametric and nonparametric estimation of causal effects in finite samples pp. 15

Rudolph Kara E., Williams Nicholas T., Miles Caleb H., Antonelli Joseph and Diaz Ivan

Bounding the probabilities of benefit and harm through sensitivity parameters and proxies pp. 16

Peña Jose M.

Efficient and flexible mediation analysis with time-varying mediators, treatments, and confounders pp. 17

Díaz Iván, Williams Nicholas and Rudolph Kara E.

Attributable fraction and related measures: Conceptual relations in the counterfactual framework pp. 18

Suzuki Etsuji and Yamamoto Eiji

Robust inference for matching under rolling enrollment pp. 19

Glazer Amanda K. and Pimentel Samuel D.

Confidence in causal inference under structure uncertainty in linear causal models with equal variances pp. 21

Strieder David and Drton Mathias

Sensitivity analysis for causal decomposition analysis: Assessing robustness toward omitted variable bias pp. 23

Park Soojin, Kang Suyeon, Lee Chioun and Ma Shujie

Quantitative probing: Validating causal models with quantitative domain knowledge pp. 23

Grünbaum Daniel, Stern Maike L. and Lang Elmar W.

Heterogeneous interventional effects with multiple mediators: Semiparametric and nonparametric approaches pp. 23

Rubinstein Max, Branson Zach and Kennedy Edward H.

Randomization-based, Bayesian inference of causal effects pp. 25

Leavitt Thomas

2D score-based estimation of heterogeneous treatment effects pp. 25

Ye Steven Siwei, Chen Yanzhen and Padilla Oscar Hernan Madrid

Minimally capturing heterogeneous complier effect of endogenous treatment for any outcome variable pp. 25

Goeun Lee, Choi Jin-young and Myoung-jae Lee

Conditional average treatment effect estimation with marginally constrained models pp. 26

C. van Amsterdam Wouter A. and Ranganath Rajesh

Robust variance estimation and inference for causal effect estimation pp. 27

Tran Linh, Petersen Maya, Schwab Joshua and J. van der Laan Mark

Precise unbiased estimation in randomized experiments using auxiliary observational data pp. 27

Gagnon-Bartsch Johann A., Sales Adam C., Wu Edward, Botelho Anthony F., Erickson John A., Miratrix Luke W. and Heffernan Neil T.

Matched design for marginal causal effect on restricted mean survival time in observational studies pp. 28

Lin Zihan, Ni Ai and Lu Bo

Model-based regression adjustment with model-free covariates for network interference pp. 29

Han Kevin and Ugander Johan

Potential outcome and decision theoretic foundations for statistical causality pp. 30

Richardson Thomas S. and Robins James M.

Adaptive normalization for IPW estimation pp. 33

Khan Samir and Ugander Johan

Causality and independence in perfectly adapted dynamical systems pp. 35

Blom Tineke and Mooij Joris M.

Exploiting neighborhood interference with low-order interactions under unit randomized design pp. 36

Cortez-Rodriguez Mayleen, Eichhorn Matthew and Yu Christina Lee

Instrumental variable regression via kernel maximum moment loss pp. 42

Zhang Rui, Imaizumi Masaaki, Schölkopf Bernhard and Muandet Krikamol

Randomized graph cluster randomization pp. 53

Ugander Johan and Yin Hao