Software

grf: Forest-based methods for causal inference

maq: Multi-armed treatment rule evaluation with Qini curves

policytree: Interpretable policy learning via optimal decision trees

balnet: Pathwise estimation of covariate balancing propensity scores

Papers

Nonparametric Regression Discontinuity Designs with Survival Outcomes
Maximilian Schuessler, Erik Sverdrup, Robert Tibshirani, and Stefan Wager
Preprint
[arxiv]

balnet: Pathwise Estimation of Covariate Balancing Propensity Scores
Erik Sverdrup and Trevor Hastie
Preprint
[arxiv]

Statistical Learning for Heterogeneous Treatment Effects: Pretraining, Prognosis, and Prediction
Maximilian Schuessler, Erik Sverdrup,  and Robert Tibshirani
Preprint
[arxiv]

Estimating the Effects of Vaping Frequency on Smoking Cessation Using PATH Study Data: A Causal Forest Approach
Thuy T. T. Le, Erik Sverdrup, Ruoyan Sun, ... , Andrew Hyland, Kenneth E. Warner, and David Mendez
Preprint
[medrxiv]

Efficient Log-Rank Updates for Random Survival Forests
Erik Sverdrup, James Yang, and Michael  LeBlanc
Journal of Computational and Graphical Statistics, forthcoming
[paper, arxiv]

Qini Curves for Multi-Armed Treatment Rules
Erik Sverdrup, Han Wu, Susan Athey, and Stefan Wager
Journal of Computational and Graphical Statistics, 34(3), 2025
[paper, arxiv, github]

Estimating Treatment Effect Heterogeneity in Psychiatry: A Review and Tutorial with Causal Forests
Erik Sverdrup, Maria Petukhova, and Stefan Wager
International Journal of Methods in Psychiatric Research, 34(2), 2025
[paper, arxiv, github]

What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work?
Susanne Dandl, Christian Haslinger, Torsten Hothorn, Heidi Seibold, Erik Sverdrup, Stefan Wager, and Achim Zeileis
Annals of Applied Statistics, 18(1), 2024
[paper, arxiv]

Estimated Average Treatment Effect of Psychiatric Hospitalization in Patients With Suicidal Behaviors: A Precision Treatment Analysis
Eric L. Ross, Robert M. Bossarte, ..., Erik Sverdrup, Stefan Wager, and Ronald C. Kessler
JAMA Psychiatry, 81(2), 2024
[paper]

A Prediction Model for Differential Resilience to the Effects of Combat-related Stressors in US Army Soldiers
Ronald C. Kessler, Robert M. Bossarte, ..., Erik Sverdrup, ..., and Robert J. Ursano.
International Journal of Methods in Psychiatric Research, 33(4), 2024
[paper]

Proof-of-concept of a Data-driven Approach to Estimate the Associations of Comorbid Mental and Physical Disorders with Global Health-related Disability
Ymkje Anna de Vries, Jordi Alonso, ..., Erik Sverdrup, ..., and Ronald C. Kessler.
International Journal of Methods in Psychiatric Research, 33(1), 2024
[paper]

Developing an Individualized Treatment Rule for Veterans with Major Depressive Disorder Using Electronic Health Records
Nur Hani Zainal, Robert M. Bossarte, ..., Erik Sverdrup, ..., and Ronald C. Kessler.
Molecular Psychiatry,  29(8), 2024
[paper]

Estimating Heterogeneous Treatment Effects with Right-Censored Data via Causal Survival Forests
Yifan Cui, Michael R. Kosorok, Erik Sverdrup, Stefan Wager, and Ruoqing Zhu
Journal of the Royal Statistical Society: Series B, 85(2), 2023
[paper, arxiv, github]

Proximal Causal Learning of Conditional Average Treatment Effects
Erik Sverdrup and Yifan Cui
International Conference on Machine Learning, 2023
[paper, arxiv]

Low-intensity Fires Mitigate the Risk of High-intensity Wildfires in California's Forests
Xiao Wu, Erik Sverdrup, Michael D. Mastrandrea, Michael W. Wara, and Stefan Wager
Science Advances, 9(45), 2023
[paper, statistical appendix, github]

Treatment Heterogeneity with Survival Outcomes
Yizhe Xu,  Nikolaos Ignatiadis, Erik Sverdrup, Scott Fleming, Stefan Wager, and Nigam Shah
Chapter in: Handbook of Matching and Weighting Adjustments for Causal Inference. Chapman & Hall/CRC Press, 2023
[book, arxiv, github]

Doubly Robust Treatment Effect Estimation with Missing Attributes
Imke Mayer, Erik Sverdrup, Tobias Gauss, Jean-Denis Moyer, Stefan Wager, and Julie Josse
Annals of Applied Statistics, 14(3), 2020
[paper, arxiv]

policytree: Policy Learning via Doubly Robust Empirical Welfare Maximization over Trees
Erik Sverdrup, Ayush Kanodia, Zhengyuan Zhou, Susan Athey, and Stefan Wager
Journal of Open Source Software, 5(50), 2020
[paper, github]

Technical documentation

An Introduction to  grf
Erik Sverdrup, Vitor Hadad, Susan Athey, Julie Tibshirani, and Stefan Wager
R  package vignette, March 2026
[CRAN]

Treatment Heterogeneity with Right-Censored Outcomes Using grf
Erik Sverdrup and Stefan Wager
Lifetime Data Science Newsletter (LiDS), January 2024
[arxiv]

Previous work in finance

Financial Intermediary Risk and the Cross-section of Hedge-fund Returns
Magnus Dahlquist, Simon Rottke, Valeri Sokolovski, and Erik Sverdrup
[ssrn]

Constrained Currency Stochastic Discount Factors
Piotr Orlowski, Valeri Sokolovski, and Erik Sverdrup
[ssrn]