Fabian Otto-Sobotka

Epidemiology and Biometry  (» Postal address)

V03 A106 (» Adress and map )

nach Vereinbarung

+49 441 798-4476  (F&P

Research Focus

  • Expectile and Quantile Regression
  • Boosting
  • Semiparametric Regression
  • Longitudinal Data and Mixed Models
  • Time to Event Analyses
  • Instrumental Variables
  • Graphical Models



  • 01/2018: Certificate for university level teaching from the University Oldenburg
  • 03/2012: Dissertation with the topic "Semiparametric Expectile Regression" at the University Oldenburg
  • 04/2009: Diploma thesis in mathematics with the topic "Validation of undirected graphical models" at BIPS / University of Bremen

Professional Career

  • since 10/2014: Postdoctoral Researcher (until 02/18 Akademischer Rat) in the Division for Epidemiology and Biometry at the Department of Health Services Research of the University Oldenburg
  • 2012–2014: Akademischer Rat at the Chair for Statistics at the Department of  Economics of the University Göttingen
  • 2009–2012: PhD student and scientific assistant at the Institute for Mathematics at the University Oldenburg
  • 2003–2009: Studies of mathematics at the Universities of Kaiserslautern und Bremen

Current Projects

  • Project for the German Research Foundation (DFG) "Verteilungsregression für Ereigniszeiten" / "Distributional regression for times to event" (together with Verena Jürgens and Antje Timmer)
  • Project for the German Research Foundation (DFG) "Strukturiert Additive Verteilungsregression" / "Structured additive distributional regression" (together with Thomas Kneib)
  • DAAD travel grant for an invited presentation at the CMStatistics 2015 in London


  • de Sordi D, Kappen S, Otto-Sobotka F, Gutierrez L, Fortuny J, Reinold J, Schink T, Timmer A. Validity of hospital Icd‐10‐Gm-codes to identify Anaphylaxis.  ISPE September 2020 ICPE; 14.09.2020.
  • de Sordi D, Kappen S, Otto-Sobotka F, Kulschewski A, Weyland A, Gutierrez L, Fortuny J, Reinold J, Schink T, Timmer A. Validity of Hospital ICD-10-GM Codes to Identify Anaphylaxis. Pharmacoepidemiology and Drug Saf. 2021;12:1643–1652.
  • Otto-Sobotka, F. Semiparametrische Verteilungsregression.  Oberseminar "Neuere Methoden der Biometrie"; 17.01.2018; Institut für Biometrie und Klinische Forschung, Universität Münster 2018.
  • Otto-Sobotka, F. Communicating distributional regression results to applied scientists. GMDS; 10.09.2019; Dortmund.
  • Otto-Sobotka, F. Semiparametric Accelerated Failure Times Quantile and Expectile Regression using Auxiliary Likelihoods. DAGStat; 20.03.2019; München.
  • Kappen S, Otto-Sobotka, F, Seipp A. Vorstellung aktueller Projekte: PSA-Testung als Früherkennungsuntersuchung, Verteilungsregression von Patientenoutcomes, Verteilungsregression für Ereigniszeiten. Kolloquium des Departments für Versorgungsforschung; 24.09.2018; Universität Oldenburg 2018.
  • Löffler BS, Stecher HI, Fudickar S, de Sordi D, Otto-Sobotka F, Hein A, Herrmann CS. Counteracting the Slowdown of Reaction Times in a Vigilance Experiment With 40 Hz Transcranial Alternating Current Stimulation. Transactions on Neural Systems & Rehabilitation Engineering. 2018;26(10):2053–2061.
  • Otto-Sobotka F, Mirkov, R., Hofner, B., Kneib, T. Modelling Flow in Gas Transmission Networks Using Shape-Constrained Expectile Regression. In: Daouia A, Ruiz-Gazen, A., editor. Advances in Contemporary Statistics and Econometrics. Cham: Springer; 2021.
  • Otto-Sobotka F, Peplies J, Timmer A. Modeling determinants of satisfaction with health care in youth with inflammatory bowel disease Part 2: semiparametric distributional regression. Clinical epidemiology. 2019;11:403.
  • Otto-Sobotka F, von Gablenz P, Holube I. Distributional regression of self-reported hearing abilities in the HÖRSTAT study. GMDS; 17.09. –21.09.2017; Oldenburg: German Medical Science GMS Publishing House; 2017.
  • Otto-Sobotka F, de Sordi D. Introduction to R. Workshop. GMDS; 17.09.-21.09.2017; Oldenburg 2017.
  • Otto-Sobotka F, Salvati N, Ranalli MG, Kneib T. Adaptive Semiparametric M-Quantile Regression. Econometrics and Statistics. 2019;11:116–129.
  • Roeper J, Falk M, Chalaris-Rissmann A, Lueers A, Wedeken K, Stropiep U, et al. TP53 co-mutations in EGFR mutated patients in NSCLC stage IV: A strong predictive factor of ORR, PFS and OS in EGFR mt+ NSCLC. Oncotarget. 2020;11(3):250–264.
  • Seipp A, Klausen A, Timmer A, Grimm T, Groß M, Summ O, Otto-Sobotka F. Effect of mechanical insufflation-exsufflation for ineffective cough on weaning duration in diseases of the peripheral or central nervous system (MEDINE): study protocol for a randomised controlled trial in a neurological weaning centre. BMJ Open. 2023;13(7):e071273.
  • Seipp A, Uslar V, Weyhe D, Timmer A, Otto-Sobotka F. Weighted expectile regression for right-censored data. Statistics in Medicine. 2021;40(25):5501–5520.
  • Seipp A, Uslar V, Weyhe D, Timmer A, Otto-Sobotka F. Flexible semiparametric mode regression for time-to-event data. Statistical Methods in Medical Research. 2022;31(12):2352–2367.
  • Seipp A, Otto-Sobotka F. Weighted Expectile Regression for Right-Censored Data. ZeSOB Doktorandenkolloquium; 30.09.2019; Bremen.
  • Seipp A, Otto-Sobotka F. Mode Regression for Overall Survival of Pancreatic Cancer Patients. ZeSOB Doktorandenkolloquium; 29.09.2020.
  • Seipp A, Otto-Sobotka F. dirttee: Distributional Regression for Time to Event Data. R package version 1.0. 2022.
  • Seipp A, Uslar V, Timmer A, Otto-Sobotka F. Mode Regression in Survival Analysis. GMDS; 06.09.2020.
  • Spiegel E, Kneib T, Otto-Sobotka F. Generalized additive models with flexible response functions. F Stat Comput. 2017:1–16.
  • Spiegel E, Kneib T, Otto-Sobotka F. Spatio-temporal expectile regression models. Statistical Modeling. 2019;20(4):386–409.
  • Spiegel E, Kneib T; von Gablenz, P; Otto-Sobotka, F. Generalized expectile regression with flexible response function Biometrical Journal. 2021;63(5):1028–1051.
  • Timmer A, de Sordi D, Menke E, Peplies J, Classen M, Koletzko S, Otto-Sobotka F. Modeling determinants of satisfaction with health care in youth with inflammatory bowel disease: a cross-sectional survey. Clinical Epidemiology. 2018;10:1289–1305.
  • Timmer A, Neuser J, Uslar V, de Sordi D, Kappen S, Seipp A, Tiles-Sar N, Beckhaus J, Otto-Sobotka F. Wissenschaftsausbildung im Medizinstudium: Das Oldenburger Datenanalyseprojekt als Umsetzungsbeispiel [Lessons learned]. GMS Med Inform Biom Epidemiol. 2023;19(Doc11).
  • Timmer A, Neuser J, Uslar V, de Sordi D, Kappen S, Seipp A, Tiles-Sar N, Beckhaus J, Otto-Sobotka F. Science education in medical school: the Oldenburg data analysis project as an implementation example [Lessons learned]. GMS Med Inform Biom Epidemiol. 2023;19(Doc11).
  • von Gablenz P, Otto-Sobotka F, Holube I. Sprachverstehen nach Selbsteinschätzung und im Göttinger Satztest in der Allgemeinbevölkerung. Jahrestagung der Deutschen Gesellschaft für Audiologie (DGA); 28.02. –03.03.2018; Halle (Saale) 2018.
  • von Gablenz P, Otto-Sobotka F, Holube I. Adjusting Expectations: Hearing Abilities in a Population-Based Sample Using an SSQ Short Form. Trends Hear. 2018;22:2331216518784837.
  • Weyhe D, Seipp A, Uslar V, Timmer A, Otto-Sobotka F. Outcome-Analyse mithilfe von Quantilregression bei 1028 Patienten mit kolorektalem Karzinom. Zeitschrift für Gastroenterologie. 2019;57(09):KV 310.
  • Wirsik N, Otto-Sobotka F, Pigeot I. Modeling physical Activity using L0-penalised expectile regression. Biometrical Journal. 2019;61(6):1371–1384.
  • Zeleke A, Worku A, Demissie A, Otto-Sobotka F, Wilken M, Lipprandt M, et al. Evaluation of Electronic and Paper Pen Data Capturing Tools for Data Quality in a Public Health Survey in a Health and Demographic Surveillance Site, Ethiopia: A randomized controlled crossover Healthcare IT-Evaluation. JMIR MHealth and Uhealth. 2019;7(2):e10995.

All current publications and conference papers can be found under publications.

Earlier Publications


Current lectures and seminars can be viewed here.


The current lectures target first year master students who want to use inductive statistics in their further studies or theses. The lectures contain basic statistic analysis methods and their applications with the software R. 

Term Title Place Time







Foundations of STS: Statistics and Programming (VL)








Mon 10–12

Thu 10–12


Committee Work


  • R-package expectreg (Sobotka, Schnabel, Schulze Waltrup with contributions from Eilers, Kneib, Kauermann)
  • R-package gmvalid (Sobotka, Foraita)
  • R-package FlexGAM (Spiegel)
  • R-package dirttee (Seipp, Otto-Sobotka)
(Changed: 19 Jan 2024)  | 
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