| Model-Based Recursive Partitioning for Subgroup Analyses H Seibold, A Zeileis, T Hothorn The international journal of biostatistics 12 (1), 45-63, 2016 | 176 | 2016 |
| Individual treatment effect prediction for amyotrophic lateral sclerosis patients H Seibold, A Zeileis, T Hothorn Statistical methods in medical research 27 (10), 3104-3125, 2018 | 73 | 2018 |
| OpenML: An R package to connect to the machine learning platform OpenML G Casalicchio, J Bossek, M Lang, D Kirchhoff, P Kerschke, B Hofner, ... Computational Statistics, 1-15, 2017 | 67 | 2017 |
| Invertebrates outcompete vertebrate facultative scavengers in simulated lynx kills in the Bavarian Forest National Park, Germany RR Ray, H Seibold, M Heurich Animal Biodiversity and Conservation 37 (1), 77-88, 2014 | 64 | 2014 |
| An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action H Anzt, F Bach, S Druskat, F Löffler, A Loewe, BY Renard, G Seemann, ... F1000Research 9, 2020 | 62 | 2020 |
| Open science in software engineering D Mendez, D Graziotin, S Wagner, H Seibold Contemporary Empirical Methods in Software Engineering, 477-501, 2020 | 61 | 2020 |
| Patterns of lynx predation at the interface between protected areas and multi-use landscapes in central Europe E Belotti, N Weder, L Bufka, A Kaldhusdal, H Küchenhoff, H Seibold, ... PloS one 10 (9), e0138139, 2015 | 42 | 2015 |
| A replication crisis in methodological research? AL Boulesteix, S Hoffmann, A Charlton, H Seibold Significance 17 (5), 18-21, 2020 | 33 | 2020 |
| Subgroup identification in clinical trials: an overview of available methods and their implementations with R Z Zhang, H Seibold, MV Vettore, WJ Song, V François Annals of Translational Medicine 6 (7), 2018 | 33 | 2018 |
| Generalised linear model trees with global additive effects H Seibold, T Hothorn, A Zeileis Advances in Data Analysis and Classification 13 (3), 703-725, 2019 | 29 | 2019 |
| On the choice and influence of the number of boosting steps for high-dimensional linear Cox-models H Seibold, C Bernau, AL Boulesteix, R De Bin Computational Statistics, 1-21, 2018 | 28* | 2018 |
| Subgroup identification in dose‐finding trials via model‐based recursive partitioning M Thomas, B Bornkamp, H Seibold Statistics in medicine 37 (10), 1608-1624, 2018 | 24 | 2018 |
| Estimating patient-specific treatment advantages in the ‘Treatment for Adolescents with Depression Study’ S Foster, M Mohler-Kuo, L Tay, T Hothorn, H Seibold Journal of psychiatric research 112, 61-70, 2019 | 22 | 2019 |
| A computational reproducibility study of PLOS ONE articles featuring longitudinal data analyses H Seibold, S Czerny, S Decke, R Dieterle, T Eder, S Fohr, N Hahn, ... Plos one 16 (6), e0251194, 2021 | 20 | 2021 |
| Association between post-operative delirium and use of volatile anesthetics in the elderly: A real-world big data approach T Saller, L Hubig, H Seibold, Z Schroeder, B Wang, P Groene, ... Journal of clinical anesthesia 83, 110957, 2022 | 15 | 2022 |
| Survival forests under test: Impact of the proportional hazards assumption on prognostic and predictive forests for amyotrophic lateral sclerosis survival N Korepanova, H Seibold, V Steffen, T Hothorn Statistical Methods in Medical Research 29 (5), 1403-1419, 2020 | 14 | 2020 |
| model4you: An R Package for Personalised Treatment Effect Estimation H Seibold, A Zeileis, T Hothorn Journal of Open Research Software 7 (1), 2019 | 14 | 2019 |
| Package ‘partykit’ T Hothorn, H Seibold, A Zeileis, MT Hothorn | 11 | 2023 |
| What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work? S Dandl, T Hothorn, H Seibold, E Sverdrup, S Wager, A Zeileis arXiv preprint arXiv:2206.10323, 2022 | 9 | 2022 |
| Statisticians, roll up your sleeves! There's a crisis to be solved H Seibold, A Charlton, AL Boulesteix, S Hoffmann Significance 18 (4), 42-44, 2021 | 7 | 2021 |
Torsten Hothorn在 R-project.org 的电子邮件经过验证
