| grf: Generalized Random Forests. R package version 2.0.2 J Tibshirani, S Athey, R Friedberg, V Hadad, D Hirshberg, L Miner, ... URL https://cran.r-project.org/web/packages/grf/grf.pdf, 2018 | 288* | 2018 |
| Estimating heterogeneous treatment effects with right-censored data via causal survival forests Y Cui, MR Kosorok, E Sverdrup, S Wager, R Zhu Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2023 | 80 | 2023 |
| policytree: Policy learning via doubly robust empirical welfare maximization over trees E Sverdrup, A Kanodia, Z Zhou, S Athey, S Wager Journal of Open Source Software 5 (50), 2232, 2020 | 57 | 2020 |
| Doubly robust treatment effect estimation with missing attributes I Mayer, E Sverdrup, T Gauss, JD Moyer, S Wager, J Josse The Annals of Applied Statistics 14 (3), 1409-1431, 2020 | 43 | 2020 |
| Treatment heterogeneity with survival outcomes Y Xu, N Ignatiadis, E Sverdrup, S Fleming, S Wager, N Shah Handbook of Matching and Weighting Adjustments for Causal Inference, 445-482, 2023 | 17 | 2023 |
| Low-intensity fires mitigate the risk of high-intensity wildfires in California’s forests X Wu, E Sverdrup, MD Mastrandrea, MW Wara, S Wager Science advances 9 (45), eadi4123, 2023 | 16 | 2023 |
| What makes forest-based heterogeneous treatment effect estimators work? S Dandl, C Haslinger, T Hothorn, H Seibold, E Sverdrup, S Wager, ... The Annals of Applied Statistics 18 (1), 506-528, 2024 | 13 | 2024 |
| Estimated average treatment effect of psychiatric hospitalization in patients with suicidal behaviors: a precision treatment analysis EL Ross, RM Bossarte, SK Dobscha, SM Gildea, I Hwang, CJ Kennedy, ... JAMA psychiatry 81 (2), 135-143, 2024 | 12 | 2024 |
| Hedge Funds and Prime Broker Risk M Dahlquist, S Rottke, V Sokolovski, E Sverdrup Swedish House of Finance Research Paper, 2023 | 12 | 2023 |
| Proximal causal learning of conditional average treatment effects E Sverdrup, Y Cui International Conference on Machine Learning, 33285-33298, 2023 | 8* | 2023 |
| The GRF algorithm J Tibshirani, S Athey, E Sverdrup, S Wager Retrieved 2020-04-25, from https://github. com/grf-labs/grf, 2020 | 6 | 2020 |
| Qini curves for multi-armed treatment rules E Sverdrup, H Wu, S Athey, S Wager Journal of Computational and Graphical Statistics, 1-24, 2024 | 4 | 2024 |
| Benchmark currency stochastic discount factors P Orłowski, V Sokolovski, E Sverdrup Available at SSRN 3945075, 2021 | 3 | 2021 |
| Estimating treatment effect heterogeneity in Psychiatry: A review and tutorial with causal forests E Sverdrup, M Petukhova, S Wager arXiv preprint arXiv:2409.01578, 2024 | 1 | 2024 |
| Hedge Funds and Financial Intermediary Risk M Dahlquist, S Rottke, V Sokolovski, E Sverdrup Stockholm School of Economics Working Paper, 2022 | 1 | 2022 |
| A prediction model for differential resilience to the effects of combat‐related stressors in US army soldiers RC Kessler, RM Bossarte, I Hwang, A Luedtke, JA Naifeh, MK Nock, ... International Journal of Methods in Psychiatric Research 33 (4), e70006, 2024 | | 2024 |
| Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records NH Zainal, RM Bossarte, SM Gildea, I Hwang, CJ Kennedy, H Liu, ... Molecular psychiatry, 1-11, 2024 | | 2024 |
| Proof‐of‐concept of a data‐driven approach to estimate the associations of comorbid mental and physical disorders with global health‐related disability YA de Vries, J Alonso, S Chatterji, P de Jonge, J Lokkerbol, JJ McGrath, ... International Journal of Methods in Psychiatric Research 33 (1), e2003, 2024 | | 2024 |
| Treatment heterogeneity with right-censored outcomes using grf E Sverdrup, S Wager arXiv preprint arXiv:2312.02482, 2023 | | 2023 |
Stefan WagerGraduate School of Business, Stanford University在 stanford.edu 的电子邮件经过验证
