Andreas Bender

About

I am a Postdoc at the Department of Statistics at LMU Munich in the working groups Computational Statistics and Statistical Consulting Unit (StaBLab). I have a Bachelor's Degree (B.Sc.) in Statistics with a minor in Computer Science, a Master's Degree (M.Sc.) in Statistics with specialization in theory and a Ph.D. (Dr.rer.nat.) in Statistics with focus on survival analysis with cumulative effects. After my Ph.D. I did a Postdoc at the Big Data Institute, University of Oxford, working on spatial analysis in the context of infectious disease mapping.

You can find more information about me on my personal website.

Contact

Institut für Statistik

Ludwig-Maximilians-Universität München

Ludwigstraße 33

D-80539 München

Andreas.Bender [at] stat.uni-muenchen.de

(+49)89 2180 3351

Research Interests

You Can Find me on

Software

References

  1. Bauer A, Bender A, Klima A, Küchenhoff H (2019) KOALA: a new paradigm for election coverage. AStA Advances in Statistical Analysis. https://doi.org/10.1007/s10182-019-00352-6.
  2. Bender A, Python A, Lindsay S, Golding N, Moyes CL (2019) Modelling geospatial distributions of the triatomine vectors of Trypanosoma cruzi in Latin America. bioRxiv, 738310. https://www.biorxiv.org/content/10.1101/738310v1.
  3. Bender A, Bauer A (2018) coalitions: Coalition probabilities in multi-party democracies. http://joss.theoj.org.
  4. Bender A, Groll A, Scheipl F (2018) A generalized additive model approach to time-to-event analysis. Statistical Modelling 18, 299–321. https://doi.org/10.1177/1471082X17748083.
  5. Bender A, Scheipl F (2018) pammtools: Piece-wise exponential Additive Mixed Modeling tools. arXiv:1806.01042 [stat]. http://arxiv.org/abs/1806.01042.
  6. Bender A, Scheipl F, Hartl W, Day AG, Küchenhoff H (2018) Penalized estimation of complex, non-linear exposure-lag-response associations. Biostatistics. https://academic.oup.com/biostatistics/advance-article/doi/10.1093/biostatistics/kxy003/4852816.
  7. Hartl WH, Bender A, Scheipl F, Kuppinger D, Day AG, Küchenhoff H (2018) Calorie intake and short-term survival of critically ill patients. Clinical Nutrition. http://www.sciencedirect.com/science/article/pii/S0261561418301353.
  8. Pratschke S, Bender A, Boesch F et al. (2018) Association between donor age and risk of graft failure after liver transplantation: An analysis of the Eurotransplant database - a retrospective cohort study. Transplant International 0. https://onlinelibrary.wiley.com/doi/abs/10.1111/tri.13357.
  9. Maierhofer T, Pfisterer F, Bender A et al. (2017) Kosten als Instrument zur Effizienzbeurteilung intensivmedizinischer Funktionseinheiten. Medizinische Klinik - Intensivmedizin und Notfallmedizin, 1–7. https://link.springer.com/article/10.1007/s00063-017-0315-8.
  10. Brandl S, Falk W, Klemmt H-J et al. (2014) Possibilities and Limitations of Spatially Explicit Site Index Modelling for Spruce Based on National Forest Inventory Data and Digital Maps of Soil and Climate in Bavaria (SE Germany). Forests 5, 2626–2646. http://www.mdpi.com/1999-4907/5/11/2626.
  11. Ruëff F, Vos B, Oude Elberink J et al. (2014) Predictors of clinical effectiveness of Hymenoptera venom immunotherapy. Clinical & Experimental Allergy 44, 736–746. http://onlinelibrary.wiley.com/doi/10.1111/cea.12275/abstract.
  12. Guillemot V, Bender A, Boulesteix A-L (2013) Iterative Reconstruction of High-Dimensional Gaussian Graphical Models Based on a New Method to Estimate Partial Correlations under Constraints. PLoS ONE 8, e60536. http://dx.doi.org/10.1371/journal.pone.0060536.
  13. Kuppinger D, Hartl WH, Bertok M et al. (2013) Nutritional screening for risk prediction in patients scheduled for extra-abdominal surgery. Nutrition 29, 399–404. http://www.nutritionjrnl.com/article/S0899-9007(12)00276-6/abstract.
  14. Bergmann S, Ziegler N, Bartels T et al. (2013) Prevalence and severity of foot pad alterations in German turkey poults during the early rearing phase. Poultry science 92, 1171–1176. Researchgate.
  15. Boulesteix A-L, Bender A, Lorenzo Bermejo J, Strobl C (2012) Random forest Gini importance favours SNPs with large minor allele frequency: impact, sources and recommendations. Briefings in Bioinformatics 13, 292–304.