Dr. Maike Hohberg

Head of Working Group "Computational Statistics"

telephone:  +49 551 3964408

fax: +49 551 394995

e-mail address: maike.hohberg@med.uni-goettingen.de

location: Humboldtallee 32, GF, 137

Portrait of Maike Hohberg, Department of Medical Statistics

Short Biography

[since 2022]
University of Goettingen, Department of Medical Statistics, Postdoctoral Researcher

Stanford University, Division of Primary Care and Population Health, Visiting Postdoctoral Researcher

University of Heidelberg, Heidelberg Institute of Global Health, Postdoctoral Researcher

University College London, Department of Statistical Science, Visiting Researcher

[since 2017]
Studies in Medicine, University of Goettingen

University of Goettingen, Chair of Statistics, Doctoral and Postdoctoral Researcher

University College London, Institute for Sustainable Resources, Doctoral Researcher

The World Bank, Research Unit - Financial and Private Sector Development, consultant [2013-2014] The World Bank, Environment Unit for Latin America and Caribbean Region, consultant and Carlo Schmid Fellow

Student Research Assistant at the German Institute of Global and Area Studies (GIGA), at the University of Hagen, and at the University of Goettingen

M.A. International Economics, University of Goettingen and Delhi School of Economics, India

B.Sc. Business Administration and Economics, University of Passau and Universidad Cátolica de Córdoba, Argentina


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

Exam Theses

Ph.D. in Applied Statistics (University of Goettingen, 2020): Advances in Regression Beyond the Mean - with Applications to Poverty and Health

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