Prof. Dr. Maike Hohberg
Gruppenleiterin AG "Computational Statistics"
Telefon: +49 551 3964408
Telefax: +49 551 3965605
E-Mail-Adresse: maike.hohberg@med.uni-goettingen.de
Ort / Raum: Humboldtallee 32, EG, 137
Kurzer Lebenslauf
[seit 2022]
UMG Göttingen, Department für Medizinische Statistik, Postdoc
[2022]
Stanford University, Division of Primary Care and Population Health, Forschungsaufenthalt
[2020 - 2022]
Universitätsklinikum Heidelberg, Heidelberger Institut für Global Health, Postdoc
[2018]
University College London, Department of Statistical Science, Forschungsaufenthalt
[seit 2017]
Studium der Humanmedizin, Universität Göttingen
[2015-2022]
Universität Göttingen, Doktorandin und Postdoc an der Professur für Statistik
[2014-2015]
University College London, Institute for Sustainable Resources, Wissenschaftliche Mitarbeiterin
[2014-2015]
The World Bank, Research Unit - Financial and Private Sector Development, Consultant
[2013-2014]
The World Bank, Environment Unit for Latin America and Caribbean Region, Washington, D.C., Consultant und Carlo-Schmid-Fellow
[2012-2013]
Studentische Hilfskraft am German Institute of Global and Area Studies (GIGA), der Fernuniversität Hagen und an der Universität Göttingen
[2010-2013]
M.A. International Economics, University of Göttingen und Delhi School of Economics, Indien
[2006-2010]
B.Sc. Business Administration and Economics, Universität Passau und Universidad Cátolica de Córdoba, Argentinien
Publikationen
Martins R., Sousa, B., Kneib, T., Hohberg, M., Klein, N., Duarte, E., Rodrigues, V.(2022): Is age at menopause decreasing?–The consequences of not completing the generational cohort. BMC Medical Research Methodology. https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-022-01658-x
Hohberg, M., Donat, F., Marra, G., Kneib, T. (2021): Beyond Unidimensional Poverty Analysis Using Distributional Copula Models for Mixed Ordered-Continuous Outcomes. Journal of the Royal Statistical Society - Series C. https://rss.onlinelibrary.wiley.com/doi/full/10.1111/rssc.12517
Briseño Sánchez, G., Hohberg, M., Groll, A., Kneib, T. (2020): Flexible instrumental variable distributional regression. Journal of the Royal Statistical Society - Series A. https://rss.onlinelibrary.wiley.com/doi/10.1111/rssa.12598
Hohberg, M., Pütz, P., Kneib, T. (2020). Treatment effects beyond the mean using distributional regression: Methods and guidance. PLOS ONE. https://journals.plos.org/plosone/article/authors?id=10.1371/journal.pone.0226514
Hohberg, M., Kneib, T., Sohn, A. (2019): Mehr als Durchschnittsstatistik. Eine kritische Einführung in Regressionsmethoden jenseits des Mittelwertes. In Petersen, D.J., Willers, D., Schmitt, E.M., Birnbaum, R., Meyerhoff, J.H.E., Gießler, S., Roth, B. (eds.): Perspektiven einer Pluralen Ökonomik, Springer VS: Wiesbaden.
Hohberg, M., Landau, K., Kneib, T., Klasen, S., Zucchini, W. (2018): Vulnerability to poverty revisited: Flexible modeling and better predictive performance. Journal of Economic Inequality. https://link.springer.com/article/10.1007%2Fs10888-017-9374-6
Krüger, L., Hohberg, M., Lehmann, W., Dresing, K. (2018): Assessing the risk for major injuries in equestrian sports. BMJ Open Sport & Exercise Medicine. https://bmjopensem.bmj.com/content/4/1/e000408
Hohberg, M., Lay, J. (2015): The Impact of Minimum Wages on Informal and Formal Labor Market Outcomes: Evidence from Indonesia. IZA Journal of Labor & Development (4): 14. https://izajold.springeropen.com/articles/10.1186/s40175-015-0036-4
Abschlussarbeiten
- Promotion (Universität Göttingen, 2020): Advances in Regression Beyond the Mean - with Applications to Poverty and Health