Prof. Dr. Elisabeth Bergherr

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  • 2023 | Preprint
    ​ ​"Spatial Joint Models through Bayesian Structured Piece-wise Additive Joint Modelling for Longitudinal and Time-to-Event Data"​
    Rappl, A.; Kneib, T. ; Lang, S.& Bergherr, E. ​ (2023)
    ​Details 
  • 2023 | Journal Article | 
    ​ ​Variable Selection and Allocation in Joint Models via Gradient Boosting Techniques​
    Griesbach, C. ; Mayr, A. & Bergherr, E. ​ (2023) 
    Mathematics, 11(2) pp. 411​.​ DOI: https://doi.org/10.3390/math11020411 
    ​Details  DOI 
  • 2023 | Conference Paper
    ​ ​A novel gradient boosting framework for generalised additive mixed models​
    Knieper, L. ; Bergherr, E. ; Hothorn, T.; Müller-Voggel, N. & Griesbach, C. ​ (2023)
    In:Bergherr, Elisabeth; Groll, Andreas; Mayr, Andreas​ (Eds.), ​Proceedings of the 37th International Workshop on Statistical Modelling. ​International Workshop on Statistical Modelling​, Dortmund, Germany.
    Proceedings of the 37th International Workshop on Statistical Modelling​: TU Dortmund University.
    ​Details 
  • 2023 | Journal Article
    ​ ​Prediction-based variable selection for component-wise gradient boosting​
    Potts, S. ; Bergherr, E. ; Reinke, C. & Griesbach, C. ​ (2023) 
    The International Journal of Biostatistics,.​ DOI: https://doi.org/10.1515/ijb-2023-0052 
    ​Details  DOI 
  • 2022 | Preprint | 
    ​ ​Penalisierte Regressions-Splines in Mischungsdichtenetzwerken​
    Seifert, Q. E. ; Thielmann, A.; Bergherr, E. ; Säfken, B.; Zierk, J.; Rauh, M.& Hepp, T.​ (2022). DOI: https://doi.org/10.21203/rs.3.rs-2398185/v1 
    ​Details  DOI 
  • 2022 | Journal Article
    ​ ​Bayesian learners in gradient boosting for linear mixed models​
    Zhang, B. ; Griesbach, C.   & Bergherr, E. ​ (2022) 
    The International Journal of Biostatistics, 0(0).​ DOI: https://doi.org/10.1515/ijb-2022-0029 
    ​Details  DOI  PMID  PMC 
  • 2022 | Journal Article | Research Paper | 
    ​ ​Adaptive step-length selection in gradient boosting for Gaussian location and scale models​
    Zhang, B. ; Hepp, T.; Greven, S. & Bergherr, E. ​ (2022) 
    Computational Statistics,.​ DOI: https://doi.org/10.1007/s00180-022-01199-3 
    ​Details  DOI 
  • 2021 | Journal Article | Research Paper
    ​ ​More than one way: exploring the capabilities of different estimation approaches to joint models for longitudinal and time-to-event outcomes​
    Rappl, A.; Mayr, A. & Waldmann, E. ​ (2021) 
    The International Journal of Biostatistics, 0(0).​ DOI: https://doi.org/10.1515/ijb-2020-0067 
    ​Details  DOI  PMID  PMC 
  • 2021 | Journal Article | Research Paper
    ​ ​Addressing cluster-constant covariates in mixed effects models via likelihood-based boosting techniques​
    Griesbach, C. ; Groll, A. & Bergherr, E. ​ (2021) 
    PLoS One, 16(7) art. e0254178​.​ DOI: https://doi.org/10.1371/journal.pone.0254178 
    ​Details  DOI  PMID  PMC 
  • 2021 | Journal Article | Research Paper
    ​ ​Gradient boosting for linear mixed models​
    Griesbach, C. ; Säfken, B. & Waldmann, E. ​ (2021) 
    The International Journal of Biostatistics, 17(2) pp. 317​-329​.​ DOI: https://doi.org/10.1515/ijb-2020-0136 
    ​Details  DOI  PMID  PMC 
  • 2021 | Journal Article | Research Paper | 
    ​ ​Joint Modelling Approaches to Survival Analysis via Likelihood-Based Boosting Techniques​
    Griesbach, C. ; Groll, A. & Bergherr, E. ​ (2021) 
    Computational and Mathematical Methods in Medicine, 2021.​ DOI: https://doi.org/10.1155/2021/4384035 
    ​Details  DOI  PMID  PMC 
  • 2020 | Conference Paper
    ​ ​Addressing cluster-constant covariates in mixed effects models via likelihood-based boosting techniques​
    Griesbach, C. ; Groll, A. & Waldmann, E. ​ (2020)
    ​Proceedings of the 35th International Workshop on Statistical Modelling. ​35th International Workshop on Statistical Modelling, IWSM2020​, Bilbao, Spain.
    ​Details 
  • 2019 | Journal Article | Research Paper | 
    ​ ​Addendum to: Approaches to Regularized Regression - A Comparison between Gradient Boosting and the Lasso​
    Hepp, T.; Schmid, M.; Gefeller, O.; Waldmann, E.   & Mayr, A.​ (2019) 
    Methods of Information in Medicine, 58(1) pp. 60​.​ DOI: https://doi.org/10.1055/s-0038-1669389 
    ​Details  DOI  PMID  PMC 
  • 2018 | Journal Article | Research Paper
    ​ ​Quantile regression: A short story on how and why​
    Waldmann, E. ​ (2018) 
    Statistical Modelling, 18(3-4) pp. 203​-218​.​ DOI: https://doi.org/10.1177/1471082x18759142 
    ​Details  DOI 
  • 2018 | Journal Article | Research Paper | 
    ​ ​Effects of whole-body electromyostimulation combined with individualized nutritional support on body composition in patients with advanced cancer: a controlled pilot trial​
    Schink, K.; Herrmann, H. J.; Schwappacher, R.; Meyer, J.; Orlemann, T.; Waldmann, E.   & Wullich, B. et al.​ (2018) 
    BMC Cancer, 18(1) pp. 886​.​ DOI: https://doi.org/10.1186/s12885-018-4790-y 
    ​Details  DOI  PMID  PMC 
  • 2018 | Journal Article | Research Paper
    ​ ​Psychosocial Variables Associated with Immunosuppressive Medication Non-Adherence after Renal Transplantation​
    Scheel, J. F.; Schieber, K.; Reber, S.; Stoessel, L.; Waldmann, E. ; Jank, S. & Eckardt, K.-U. et al.​ (2018) 
    Frontiers in Psychiatry, 9 pp. 23​.​ DOI: https://doi.org/10.3389/fpsyt.2018.00023 
    ​Details  DOI  PMID  PMC 
  • 2018 | Journal Article | Research Paper
    ​ ​Circadian profiling reveals higher histamine plasma levels and lower diamine oxidase serum activities in 24% of patients with suspected histamine intolerance compared to food allergy and controls​
    Pinzer, T. C.; Tietz, E.; Waldmann, E. ; Schink, M.; Neurath, M. F. & Zopf, Y.​ (2018) 
    Allergy, 73(4) pp. 949​-957​.​ DOI: https://doi.org/10.1111/all.13361 
    ​Details  DOI  PMID  PMC 
  • 2017 | Journal Article
    ​ ​Bayesian regularisation in geoadditive expectile regression​
    Waldmann, E. ; Sobotka, F. & Kneib, T. ​ (2017) 
    Statistics and Computing, 27(6) pp. 1539​-1553​.​ DOI: https://doi.org/10.1007/s11222-016-9703-9 
    ​Details  DOI 
  • 2017 | Journal Article | Research Paper | 
    ​ ​Predictive Modelling Based on Statistical Learning in Biomedicine​
    Gefeller, O.; Hofner, B.; Mayr, A. & Waldmann, E. ​ (2017) 
    Computational and Mathematical Methods in Medicine, 2017 art. 4041736​.​ DOI: https://doi.org/10.1155/2017/4041736 
    ​Details  DOI  PMID  PMC 
  • 2017 | Journal Article | Research Paper
    ​ ​Co-occurrence of viruses and mosquitoes at the vectors' optimal climate range: An underestimated risk to temperate regions?​
    Blagrove, M. S. C.; Caminade, C.; Waldmann, E. ; Sutton, E. R.; Wardeh, M. & Baylis, M.​ (2017) 
    PLoS Neglected Tropical Diseases, 11(6) art. e0005604​.​ DOI: https://doi.org/10.1371/journal.pntd.0005604 
    ​Details  DOI  PMID  PMC 
  • 2017 | Journal Article | Research Paper | 
    ​ ​An Update on Statistical Boosting in Biomedicine​
    Mayr, A.; Hofner, B.; Waldmann, E. ; Hepp, T.; Meyer, S. & Gefeller, O.​ (2017) 
    Computational and Mathematical Methods in Medicine, art. 6083072​.​ DOI: https://doi.org/10.1155/2017/6083072 
    ​Details  DOI  PMID  PMC 
  • 2017 | Journal Article
    ​ ​Boosting joint models for longitudinal and time-to-event data​
    Taylor-Robinson, D.; Pressler, T.; Schmid, M.; Mayr, A.; Waldmann, E. ; Klein, N.   & Kneib, T. ​ (2017) 
    Biometrical Journal, 59(6) pp. 1104-1121​-1121​.​ DOI: https://doi.org/10.1002/bimj.201600158 
    ​Details  DOI  PMID  PMC 
  • 2017 | Journal Article | Research Paper | 
    ​ ​Patient-reported non-adherence and immunosuppressant trough levels are associated with rejection after renal transplantation​
    Scheel, J.; Reber, S.; Stoessel, L.; Waldmann, E. ; Jank, S.; Eckardt, K.-U. & Grundmann, F. et al.​ (2017) 
    BMC Nephrology, 18(1) pp. 107​.​ DOI: https://doi.org/10.1186/s12882-017-0517-6 
    ​Details  DOI  PMID  PMC 
  • 2016 | Journal Article | Research Paper
    ​ ​Sinus surgery postpones chronic Gram-negative lung infection: cohort study of 106 patients with cystic fibrosis​
    Alanin, M. C.; Aanaes, K.; Høiby, N.; Pressler, T.; Skov, M.; Nielsen, K. G. & Taylor-Robinson, D. et al.​ (2016) 
    Rhinology, 54(3) pp. 206​-213​.​ DOI: https://doi.org/10.4193/rhin15.347 
    ​Details  DOI  PMID  PMC 
  • 2016 | Journal Article | Research Paper
    ​ ​Comparing the harmful effects of nontuberculous mycobacteria and Gram negative bacteria on lung function in patients with cystic fibrosis​
    Qvist, T.; Taylor-Robinson, D.; Olesen, H. V.; Hansen, C. R.; Mathiesen, I. H.; Høiby, N. & Katzenstein, T. L. et al.​ (2016) 
    Journal of Cystic Fibrosis, 15(3) pp. 380​-385​.​ DOI: https://doi.org/10.1016/j.jcf.2015.09.007 
    ​Details  DOI  PMID  PMC 
  • 2016 | Journal Article | Research Paper
    ​ ​Approaches to Regularized Regression - A Comparison between Gradient Boosting and the Lasso​
    Hepp, T.; Schmid, M.; Gefeller, O.; Waldmann, E.   & Mayr, A.​ (2016) 
    Methods of Information in Medicine, 55(5) pp. 422​-430​.​ DOI: https://doi.org/10.3414/me16-01-0033 
    ​Details  DOI  PMID  PMC 
  • 2016 | Journal Article | Research Paper
    ​ ​Distinct Effects of Chronic Dopaminergic Stimulation on Hippocampal Neurogenesis and Striatal Doublecortin Expression in Adult Mice​
    Salvi, R.; Steigleder, T.; Schlachetzki, J. C. M.; Waldmann, E. ; Schwab, S.; Winner, B. & Winkler, J. et al.​ (2016) 
    Frontiers in Neuroscience, 10 pp. 77​.​ DOI: https://doi.org/10.3389/fnins.2016.00077 
    ​Details  DOI  PMID  PMC 
  • 2015 | Journal Article
    ​ ​Variational approximations in geoadditive latent Gaussian regression: mean and quantile regression​
    Waldmann, E.   & Kneib, T. ​ (2015) 
    Statistics and Computing, 25(6) pp. 1247​-1263​.​ DOI: https://doi.org/10.1007/s11222-014-9480-2 
    ​Details  DOI 
  • 2015 | Journal Article
    ​ ​Differential effects of environmental heterogeneity on global mammal species richness​
    Stein, A.; Beck, J.; Meyer, C.; Waldmann, E. ; Weigelt, P.   & Kreft, H. ​ (2015) 
    Global Ecology and Biogeography, 24(9) pp. 1072​-1083​.​ DOI: https://doi.org/10.1111/geb.12337 
    ​Details  DOI 
  • 2014 | Journal Article
    ​ ​Bayesian bivariate quantile regression​
    Waldmann, E.   & Kneib, T. ​ (2014) 
    Statistical Modelling, 15(4) pp. 326​-344​.​ DOI: https://doi.org/10.1177/1471082x14551247 
    ​Details  DOI 
  • 2013 | Journal Article | 
    ​ ​Bayesian semiparametric additive quantile regression​
    Yue, Y. R.; Lang, S.; Flexeder, C.; Waldmann, E.   & Kneib, T. ​ (2013) 
    Statistical Modelling, 13(3) pp. 223​-252​.​ DOI: https://doi.org/10.1177/1471082x13480650 
    ​Details  DOI 

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