Eine gesamthafte Übersicht der Publikationen finden Sie hier.
2023
Falk Hemker, Timo Haselhoff, Susanne Brunner, Bryce T. Lawrence, Katja Ickstadt, Susanne Moebus. The role of traffic volume on sound pressure level reduction before and during COVID-19 lockdown measures in Bochum, Germany, 2023, Environmental Science and Engineering
2022
S. M. Seyedpour, C. Henning, P. Kirmizakis, S. Herbrandt, K. Ickstadt, R. Doherty and T. Ricken. Uncertainty with Varying Subsurface Permeabilities Reduced Using Coupled Random Field and Extended Theory of Porous Media contaminant transport models, Water 2023, 15(1), 159. https://doi.org/ 10.3390/w15010159
Weber, F., Ickstadt, K., & Glass, Ä. (2022). shinybrms: Fitting Bayesian regression models using a graphical user interface for the R package brms, The R Journal, 14/(2), 96–120. https://doi.org/10.32614/RJ-2022-027
Sarah Friedrich, Andreas Groll, Katja Ickstadt, Thomas Kneib, Markus Pauly, Jörg Rahnenführer, Tim Friede, Regularization approaches in clinical biostatistics: A review of methods and their applications, Statistical Methods in Medical Research, SAGE journals, 2022, https://doi.org/10.1177/09622802221133557
Jonas Kupschus, Stefan Janssen, Andreas Hoek, Jan Kuska, Jonathan Rathjens, Carsten
Sonntag, Katja Ickstadt et al. Rapid detection and online analysis of microbial changes through flow cytometry, Cytometry: Part A , Volume 101 - Issue 12, 2022, https://doi.org/10.1002/cyto.a.24704
D. Djeudeu, S. Moebus, K. Ickstadt, Multilevel Conditional Autoregressive models for longitudinal and spatially referenced epidemiological data, Spatial and Spatio-temporal Epidemiology, Volume 41, 2022, 100477, ISSN 1877-5845, https://doi.org/10.1016/j.sste.2022.100477.
Silvia Chines, Christiane Ehrt, Marco Potowski,Katja Ickstadt, Susanne Brunner, et al. Navigating Chemical Reaction Space – Application to DNA-encoded Chemistry. Chemical Science, 2022, DOI: 10.1039/D2SC02474H
Djeudeu, D. (2022). Spatial and spatio-temporal regression modelling with conditional autoregressive random effects for epidemiological and spatially referenced data (Publisher’s Version) [Universitätsbibliothek Dortmund]. https://doi.org/10.17877/de290r-22855
Ickstadt, K., Müller, H., & Weinert, H. (2022). Data Literacy. In C. Weihs (Ed.), Statistische Datenanalyse im Journalismus (Publisher’s Version, 1st ed., pp. 29–42). Springer VS. https://doi.org/10.1007/978-3-662-64693-9_3
Ickstadt, K., Pauly, M., Motta, M., Herbrandt, S., Moroff, N., Niemann, F., Henke, M., & Ten Hompel, M. (2022). Lernverfahren der Künstlichen Intelligenz zur Inwertsetzung von Daten: automatisierte Erkennung und Prognose. In M. Ten Hompel, M. Henke, & B. Otto (Eds.), Silicon Economy (Publisher’s Version, pp. 229–250). Springer Vieweg. https://doi.org/10.1007/978-3-662-63956-6_11
Thomas, M., Bornkamp, B., & Ickstadt, K. (2022). Identifying treatment effect heterogeneity in dose-finding trials using Bayesian hierarchical models. Pharmaceutical Statistics, 21(1), 17–37. https://doi.org/10.1002/pst.2150
