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Publikationen

2022

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 applicationsStatistical 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

Lau, M., Wigmann, C., Kress, S., Schikowski, T., & Schwender, H. (2022). Evaluation of tree-based statistical learning methods for constructing genetic risk scores [OnlineRessource]. BMC Bioinformatics23, Article 97. https://doi.org/10.1186/s12859-022-04634-w

Thomas, M., Bornkamp, B., & Ickstadt, K. (2022). Identifying treatment effect heterogeneity in dose-finding trials using Bayesian hierarchical models. Pharmaceutical Statistics21(1), 17–37. https://doi.org/10.1002/pst.2150

2021

Friedrich, S., Antes, G., Behr, S., Binder, H., Brannath, W., Dumpert, F., Ickstadt, K., Kestler, H. A., Lederer, J., Leitgöb, H., Pauly, M., Steland, A., Wilhelm, A., & Friede, T. (2021). Is there a role for statistics in artificial intelligence? Advances in Data Analysis and Classification. Published. https://doi.org/10.1007/s11634-021-00455-6

Heinrich, J., Maurer, R., Leckey, K., Müller, C. H., & Ickstadt, K. (2021). Detektieren ermüdungsbedingter Spannstahlbrüche mittels Rissmonitoring im Versuch und am Bauwerk. Bauingenieur96(3), 92–101. https://doi.org/10.37544/0005-6650-2021-03-60

Madjar, K., Zucknick, M., Ickstadt, K., & Rahnenführer, J. (2021). Combining heterogeneous subgroups with graph‑structured variable selection priors for Cox regression. BMC Bioinformatics22, Article 586. https://doi.org/10.1186/s12859-021-04483-z

Rathjens, J. (2021). River-mediated dynamic environmental factors and perinatal data analysis (Publisher’s Version) [Universitätsbibliothek Dortmund]. https://doi.org/10.17877/de290r-22453

Rathjens, J., Becker, E., Kolbe, A., Ickstadt, K., & Hölzer, J. (2021). Spatial and temporal analyses of perfluorooctanoic acid in drinking water for external exposure assessment in the Ruhr metropolitan area, Germany: the ‘PerSpat’-Project. Stochastic Environmental Research and Risk Assessment35(6), 1127–1143. https://doi.org/10.1007/s00477-020-01932-8

Weber, F., Knapp, G., Glass, Ä., Kundt, G., & Ickstadt, K. (2021). Interval estimation of the overall treatment effect in random-effects meta‐analyses: recommendations from a simulation study comparing frequentist, Bayesian, and bootstrap methods. Research Synthesis Methods12(3), 291–315. https://doi.org/10.1002/jrsm.1471

Wunder, J., Pemp, D., Cecil, A., Mahdiani, M., Hauptstein, R., Schmalbach, K., Geppert, L., Ickstadt, K., Esch, H. L., Dandekar, T., & Lehmann, L. (2021). Influence of breast cancer risk factors on proliferation and DNA damage in human breast glandular tissues: role of  intracellular estrogen levels, oxidative stress and estrogen biotransformation. Archives of Toxicology. In press. https://doi.org/10.1007/s00204-021-03198-7

2020

Djeudeu, D., Engel, M., Jöckel, K.-H., Moebus, S., & Ickstadt, K. (2020). Spatio-temporal analysis of the risk of depression at district-level and association with greenness based on the Heinz Nixdorf recall study. Spatial and spatio-temporal epidemiology, 33(June), 100340–100340. doi:10.1016/j.sste.2020.100340

Fermín R., Y. Y., & Ickstadt, K. (2020). Nonparametric dynamic Bayesian networks approximate protein interaction networks in a simulation study. Annals of biometrics and biostatistics, 5(1), 1031_1–1031_8. https://www.jscimedcentral.com/Biometrics/biometrics-5-1031.pdf

Geppert, L., Ickstadt, K., Munteanu, A., & Sohler, C. (2020a). Streaming statistical models via Merge & Reduce.   International journal of data science and analytics, 10(4), 331–347. doi:10.1007/s41060-020-00226-0

Geppert, L., Ickstadt, K., Munteanu, A., & Sohler, C. (2020b). Streaming statistical models via merge & reduce.   International journal of data science and analytics, 2020, 324. doi:10.1007/s41060-020-00226-0

Pemp, D., Geppert, L., Wigmann, C., Kleider, C., Hauptstein, R., Schmalbach, K., et al. (2020). Influence of breast cancer risk factors and intramammary biotransformation on estrogen homeostasis in the human breast. Archives of toxicology, 94(9), 3013–3025. doi:10.1007/s00204-020-02807-1

Rathjens, J., Becker, E., Kolbe, A., Ickstadt, K., & Hölzer, J. (2020a). Spatial and temporal analyses of perfluorooctanoic acid in drinking water for external exposure assessment in the Ruhr metropolitan area, Germany. Stochastic environmental research and risk assessment. doi:10.1007/s00477-020-01932-8

Rathjens, J., Becker, E., Kolbe, A., Ickstadt, K., & Hölzer, J. (2020b). Spatial and temporal analyses of perfluorooctanoic acid in drinking water for external exposure assessment in the Ruhr metropolitan area, Germany. Stochastic environmental research and risk assessment, 2021. doi:10.1007/s00477-020-01932-8

Schuldt, K., Behrens, T., Taeger, D., Jankovic, N., Ickstadt, K., & Stang, A. (2020). PhD program “Epidemiology & Clinical Research” at the University Hospital Essen. GMS Medizinische Informatik, Biometrie und Epidemiologie, 16(1), Doc04. doi:10.3205/mibe000207

Schwender, H., & Ickstadt, K. (2020). A novel algorithmic approach to Bayesian logic regression: invited discussion on the paper by Hubin, A., Storvik, G., Frommlet, F.; [Diskussionsbeitrag]. Bayesian analysis, 15(1), 302–306. doi:10.1214/18-ba1141

Tug, T., Ickstadt, K., Kunz, M., Sutter, A., & Igl, B.-W. (2020). Statistical analysis of in vivo alkaline comet assay data - comparison of median and geometric mean as centrality measures. Regulatory toxicology and pharmacology, 118, 104808. doi:10.1016/j.yrtph.2020.104808

Weber, F., Knapp, G., Glass, Ä., Kundt, G., & Ickstadt, K. (2020). Interval estimation of the overall treatment effect in random-effects meta‐analyses: recommendations from a simulation study comparing frequentist, Bayesian, and bootstrap methods. Research synthesis methods. doi:10.1002/jrsm.1471

Weber, F., Knapp, G., Ickstadt, K., Kundt, G., & Glass, Ä. (2020). Zero‐cell corrections in random‐effects meta‐analyses. Research synthesis methods, 11(6), 913–919. doi:10.1002/jrsm.1460

2019

Basaran, N., Duydu, Y., Üstündag, A., Taner, G., Aydin, S., Anlar, H. G., et al. (2019). Evaluation of the DNA damage in lymphocytes, sperm and buccal cells of workers under environmental and occupational boron exposure conditions. Mutation research / Genetic toxicology and environmental mutagenesis, 843, 33–39. doi:10.1016/j.mrgentox.2018.12.013

Duydu, Y., Başaran, N., Yalçın, C. Ö., Üstündağ, A., Aydın, S., Anlar, H. G., et al. (2019). Boron-exposed male workers in Turkey: no change in sperm Y:X chromosome ratio and in offspring’s sex ratio. Archives of toxicology, 93(3), 743–751. doi:10.1007/s00204-019-02391-z

Gnändinger, P., Geppert, L., & Ickstadt, K. (2019). Die Angst der Spieler beim Elfmeter: Welcher Schütze und welcher Torwart sind die Besten? In W. Krämer & C. Weihs (Eds.), Faszination Statistik: Einblicke in aktuelle Forschungsfragen und Erkenntnisse (pp. 67–74). doi:10.1007/978-3-662-60562-2_9

Hüls, A., Sugiri, D., Abramson, M. J., Hoffmann, B., Schwender, H., Ickstadt, K., et al. (2019). Benefits of improved air quality on aging lungs: impacts of genetics and obesity. bioRxiv beta, 2019. doi:10.1101/521328

Kolbe, A., Rathjens, J., Becker, E., Bücker-Nott, H., Ickstadt, K., & Hölzer, J. (2019). PFOA exposure assessment in North Rhine-Westphalia, Germany, linking birth registry data with tap water concentrations. Environmental epidemiology, 3(Supplement 1), 212. doi:10.1097/ href="01.ee9.0000608176.41536.ae">01.ee9.0000608176.41536.ae

Pemp, D., Kleider, C., Schmalbach, K., Hauptstein, R., Geppert, L., Köllmann, C., et al. (2019). Qualitative and quantitative differences in estrogen biotransformation in human breast glandular and adipose tissues: implications for studies using mammary biospecimens. Archives of toxicology, 93(10), 2823–2833. doi:10.1007/s00204-019-02564-w

Rathjens, J., Becker, E., Kolbe, A., Olthoff, K., Bergmann, S., Hölzer, J., & Ickstadt, K. (2019). Spatio-temporal smoothing of drinking water contamination data. In 5th joint statistical meeting, march 18-22, Munich:  DAGStat 2019; statistics under one umbrella; book of abstracts (p. 91).

Rathjens, J., Becker, E., Kolbe, A., Olthoff, K., Bergmann, S., Ickstadt, K., & Hölzer, J. (2019). Spatio-temporal data modelling and prediction of PFOA drinking water contamination. Environmental epidemiology, 3(Supplement 1), 327. doi:10.1097/01.ee9.0000609588.69457.a3

Schmidt, A., Henning, C., Herbrandt, S., Könke, C., Ickstadt, K., Ricken, T., & Lahmer, T. (2019). Numerical studies of earth structure assessment via the theory of porous media using fuzzy probability based random field material descriptions. GAMM-Mitteilungen / Gesellschaft für Angewandte Mathematik und Mechanik, 42(1), e201900007_1–e201900007_15. doi:10.1002/gamm.201900007

Selinski, S., Ickstadt, K., & Golka, K. (2019). Mit Statistik dem Wirken der Gene auf der Spur. In W. Krämer & C. Weihs (Eds.), Faszination Statistik: Einblicke in aktuelle Forschungsfragen und Erkenntnisse (pp. 41–49). doi:10.1007/978-3-662-60562-2_6

Tietz, T., Selinski, S., Golka, K., Hengstler, J. G., Gripp, S., Ickstadt, K., et al. (2019). Identification of interactions of binary variables associated with survival time using survivalFS. Archives of toxicology, 93(3), 585–602. doi:10.1007/s00204-019-02398-6

Weihs, C. (2019). Applications in statistical computing: from music data analysis to industrial quality improvement ; published in honor of Claus Weihs, professor of computational statistics at TU Dortmund University. (N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, & M. Vichi, Eds.)Studies in classification, data analysis, and knowledge organization (1. ed.). Cham: Springer. https://www.springer.com/gp/book/9783030251468

Weihs, C., & Ickstadt, K. (2019). Ist Data Science mehr als Statistik? Ein Blick über den Tellerrand. In W. Krämer & C. Weihs (Eds.), Faszination Statistik: Einblicke in aktuelle Forschungsfragen und Erkenntnisse (pp. 203–210). doi:10.1007/978-3-662-60562-2_26

Wigmann, C., Lange, L., Vautz, W., & Ickstadt, K. (2019). Modelling and classification of GC/IMS breath gas measurements for lozenges of different flavours. In N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, & M. Vichi (Eds.), Applications in statistical computing: from music data analysis to industrial quality improvement ; published in honor of Claus Weihs, professor of computational statistics at TU Dortmund University (pp. 31–48). doi:10.1007/978-3-25147-5_3

2018

Duydu, Y., Başaran, N., Aydın, S., Üstündağ, A., Yalçın, C. Ö., Anlar, H. G., Ickstadt, K., et al. (2018). Evaluation of FSH, LH, testosterone levels and semen parameters in male boron workers under extreme exposure conditions. Archives of toxicology, 92(10), 3051–3059. doi:10.1007/s00204-018-2296-7

Duydu, Y., Başaran, N., Üstündağ, A., Aydın, S., Yalçın, C. Ö., Anlar, H. G., Ickstadt, K., et al. (2018). Birth weights of newborns and pregnancy outcomes of environmentally boron-exposed females in Turkey. Archives of toxicology, 92(8), 2475–2485. doi:10.1007/s00204-018-2238-4

Henning, C., Herbrandt, S., Ickstadt, K., & Ricken, T. (2018). Combining finite elements and random fields to quantify uncertainty in a multi-phase structural analysis. Proceedings in applied mathematics and mechanics, 18(1), e201800333. doi:10.1002/pamm.201800333

Hermann, S., Ickstadt, K., & Müller, C. H. (2018). Bayesian prediction for a jump diffusion process: with application to crack growth in fatigue experiments. Reliability engineering & system safety, 179, 83–96. doi:10.1016/j.ress.2016.08.012

Ickstadt, K., Schäfer, M., & Zucknick, M. (2018). Toward integrative Bayesian analysis in molecular biology. Annual review of statistics and its application, 5, 141–167. doi:10.1146/annurev-statistics-031017-100438

Siebert, S., Ickstadt, K., Schäfer, M., Radon, Y., & Verveer, P. (2018). Comparison of clustering approaches with application to dual colour protein data. IET systems biology, 12(1), 7–17. doi:10.1049/iet-syb.2017.0019

Weihs, C., & Ickstadt, K. (2018). Data Science: the impact of statistics.   International journal of data science and analytics, 6(3), 189–194. doi:10.1007/s41060-018-0102-5

Wichert, K., Herold, R., Terschüren, C., Ickstadt, K., Pesch, B., Lo, W., et al. (2018). Die Rolle von Genen der Melatonin-Biosynthese bei der Entstehung von Brustkrebs. In P. Angerer & T. Muth (Eds.), 58. Wissenschaftliche Jahrestagung 2018 der Deutschen Gesellschaft für Arbeitsmedizin und Umweltmedizin e.V.: Dokumentation der Vorträge und Poster (pp. 161–162).

2017

Geppert, L., Ickstadt, K., Munteanu, A., Quedenfeld, J., & Sohler, C. (2017). Random projections for Bayesian regression. Statistics and computing, 27(1), 79–101. doi:10.1007/s11222-015-9608-z

Golka, K., Ickstadt, K., Selinski, S., Hengstler, J. G., & Wilhelm, M. (2017). Third symposium on Environmental Toxicology in North Rhine-Westphalia, Germany: Interdisciplinary Research Activities in Toxicology, Statistics, Hygiene and Medicine; meeting report on a symposium held in Dortmund May 7–8, 2015. Archives of toxicology, 91(11), 3711–3715. doi:10.1007/s00204-017-2093-8

Heinrich, J., Maurer, R., Hermann, S., Ickstadt, K., & Müller, C. H. (2017). Resistance of prestressed concrete structures to fatigue in domain of endurance limit. In D. A. Hordijk & M. Luković (Eds.), High tech concrete: where technology and engineering meet: proceedings of the 2017 fib Symposium, held in Maastricht, The Netherlands, June 12–14, 2017 (pp. 1784–1792).

Hüls, A., Frömke, C., Ickstadt, K., Hille, K., Hering, J., von Münchhausen, C., et al. (2017). Antibiotic resistances in livestock: a comparative approach to identify an appropriate regression model for count data. Frontiers in veterinary science, 4. doi:10.3389/fvets.2017.00071

Hüls, A., Ickstadt, K., Schikowski, T., & Krämer, U. (2017). Detection of gene-environment interactions in the presence of linkage disequilibrium and noise by using genetic risk scores with internal weights from elastic net regression. BMC genetics, 18, 55_1–55_14. doi:10.1186/s12863-017-0519-1

Hüls, A., Krämer, U., Carlsten, C., Schikowski, T., Ickstadt, K., & Schwender, H. (2017). Comparison of weighting approaches for genetic risk scores in gene-environment interaction studies. BMC genetics, 18, 115_1–115_12. doi:10.1186/s12863-017-0586-3

Jabs, V., Edlund, K., König, H., Grinberg, M., Madjar, K., Rahnenführer, J., et al. (2017). Integrative analysis of genome-wide gene copy number changes and gene expression in non-small cell lung cancer. PLoS one, 12(11), e0187246. doi:10.1371/journal.pone.0187246

Rekowski, J., Köllmann, C., Bornkamp, B., Ickstadt, K., & Scherag, A. (2017). Phase II dose–response trials: A simulation study to compare analysis method performance under design considerations. Journal of biopharmaceutical statistics, 1–17. doi:10.1080/10543406.2017.1293078

Schlieker, L., Telaar, A., Lueking, A., Schulz-Knappe, P., Theek, C., & Ickstadt, K. (2017). Multivariate binary classification of imbalanced datasets: a case study based on high-dimensional multiplex autoimmune assay data. Biometrical journal, 59(5), 948–966. doi:10.1002/bimj.201600207

Selinski, S., Blaszkewicz, M., Ickstadt, K., Gerullis, H., Otto, T., Roth, E., et al. (2017). Identification and replication of the interplay of four genetic high-risk variants for urinary bladder cancer. Carcinogenesis, 38(12), 1167–1179. doi:10.1093/carcin/bgx102

Treppmann, T., Ickstadt, K., & Zucknick, M. (2017). Integration of multiple genomic data sources in a Bayesian cox model for variable selection and prediction. Computational and mathematical methods in medicine, 2017. doi:10.1155/2017/7340565

2016

Duydu, Y., Basaran, N., Üstündag, A., Aydin, S., Ündeger, Ü., Yavuz Ataman, O., et al. (2016). Is Boric acid toxic to reproduction in humans?: Assessment of the Animal Reproductive toxicity data and epidemiological study results. Current drug delivery, 13(3), 324–329.

Hermann, S., Ickstadt, K., & Müller, C. H. (2016). Bayesian prediction of crack growth based on a hierarchical diffusion model. Applied stochastic models in business and industry, 32(4), 494–510. doi:10.1002/asmb.2175

Hüls, A., Krämer, U., Stolz, S., Hennig, F., Hoffmann, B., Ickstadt, K., et al. (2016). Applicability of the Global Lung Initiative 2012 reference values for spirometry for longitudinal data of elderly women. PLoS one, 11(6), e0157569. doi:10.1371/journal.pone.0157569

Kolbe, A., Rathjens, J., Becker, E.-M., Bücker-Nott, H.-J., Olthoff, K., Wilhelm, M., et al. (2016). Exposure to PFOA and birth outcome in North Rhine-Westphalia, Germany. In Abstracts of the 28th Annual Conference of the International Society for Environmental Epidemiology (ISEE), 1-4 September 2016, Rome, Italy. doi:10.1289/isee.2016.4396

Köllmann, C., Ickstadt, K., & Fried, R. (2016). Beyond unimodal regression: modelling multimodality with piecewise unimodal regession or deconvolution models. https://arxiv.org/abs/1606.01666

Koppers, L., Wormer, H., & Ickstadt, K. (2016). Towards a systematic screening tool for quality assurance and semiautomatic fraud detection for images in the life sciences. Science and engineering ethics, 23(4), 1113–1128. doi:10.1007/s11948-016-9841-7

Rathjens, J., Becker, E., Kolbe, A., Olthoff, K., Wilhelm, M., Ickstadt, K., & Hölzer, J. (2016, December 2). Smoothing applications for irregular time series with measurement errors. Presented at the Workshop “Errors in Variables.” http://www.biometrische-gesellschaft.de/fileadmin/AG_Daten/BayesMethodik/workshops_etc/2016-12_Mainz/Rathjens2016-abstract.pdf

Rathjens, J., Becker, E.-M., Bücker-Nott, H.-J., Goeken, N., Hölzer, J., Ickstadt, K., et al. (2016, March 15). Spatial modelling for birth weights, PFASs water contamination, and their dependence. Presented at the DAGStat.

2015

Casjens, S., Schwender, H., Brüning, T., & Ickstadt, K. (2015). A novel crossover operator based on variable importance for evolutionary multi-objective optimization with tree representation. Journal of heuristics, 21(1), 1–24. doi:10.1007/s10732-014-9269-7

Fried, R., Aguesop, I., Bornkamp, B., Fokianos, K., Fruth, J., & Ickstadt, K. (2015). Retrospective Bayesian outlier detection in INGARCH series. Statistics and computing, 25(2), 365–374. doi:10.1007/s11222-013-9437-x

Heeke, G., Hermann, S., Heinrich, J., Ickstadt, K., Maurer, R., & Müller, C. H. (2015). Stochastic modeling and statistical analysis of fatigue tests on prestressed concrete beams under cyclic loadings. Discussion paper / SFB 823 (Vol. 2015,25). Dortmund. doi:10.17877/DE290R-7624

Hermann, S., Ickstadt, K., & Müller, C. H. (2015a). Bayesian prediction for a jump diffusion process with application to crack growth in fatigue experiments. Discussion paper / SFB 823 (Vol. 2015,30). Dortmund. doi:10.17877/DE290R-16271

Hermann, S., Ickstadt, K., & Müller, C. H. (2015b). Prediction of crack growth based on a hierarchical diffusion model. Discussion paper / SFB 823 (Vol. 2015,4). Dortmund. doi:10.17877/DE290R-6907

Schäfer, M., Radon, Y., Klein, T., Herrmann, S., Schwender, H., Verveer, P., & Ickstadt, K. (2015). A Bayesian mixture model to quantify parameters of spatial clustering. Computational statistics & data analysis, 92, 163–176. doi:10.1016/j.csda.2015.07.004

Wieczorek, J., Malik-Sheriff, R. S., Fermin, Y., Grecco, H. E., Zamir, E., & Ickstadt, K. (2015). Uncovering distinct protein-network topologies in heterogeneous cell populations. BMC systems biology, 9(1), 24. doi:10.1186/s12918-015-0170-2

2014

Herrmann, S., Schwender, H., Ickstadt, K., & Müller, P. (2014). A Bayesian changepoint analysis of ChIP-Seq data of Lamin B. Biochimica et biophysica acta / Proteins and proteomics, 1844(1A), 138–144. doi:10.1016/j.bbapap.2013.09.001

Hoffmann, J.-E., Fermin, Y., Lo Stricker, R., Ickstadt, K., & Zamir, E. (2014). Symmetric exchange of multi-protein building blocks between stationary focal adhesions and the cytosol. eLife, 3, e02257_1–e02257_18. doi:10.7554/eLife.02257

Klein, H.-U., Schäfer, M., Porse, B. T., Hasemann, M. S., Ickstadt, K., & Dugas, M. (2014). Integrative analysis of histone ChIP-seq and transcription data using Bayesian mixture models. Bioinformatics, 30(8), 1154–1162. doi:10.1093/bioinformatics/btu003

Köllmann, C., Bornkamp, B., & Ickstadt, K. (2014). Unimodal regression using Bernstein-Schoenberg splines and penalties. Biometrics, 70(4), 783–793.

Köllmann, C., Ickstadt, K., & Fried, R. (2014). Beyond unimodal regression: modelling multimodality with piecewise unimodal, mixture or additive regression. Technical report / Sonderforschungsbereich 876 Verfügbarkeit von Information durch Analyse unter Ressourcenbeschränkung (Vol. 8). Dortmund.

Malina, M., Ickstadt, K., Schwender, H., Posch, M., & Bogdan, M. (2014). Detection of epistatic effects with logic regression and a classical linear regression model. Statistical applications in genetics and molecular biology, 13(1), 83–104. doi:10.1515/sagmb-2013-0028

Selinski, S., Blaszkewicz, M., Ickstadt, K., Hengstler, J. G., & Golka, K. (2014). Improvements in algorithms for phenotype inference: the NAT2 example. Current drug metabolism, 15(2), 233–249. doi:10.2174/1389200215666140202215717

Sturtz, S., & Ickstadt, K. (2014). Comparison of Bayesian methods for flexible modeling of spatial risk surfaces in disease mapping. Biometrical journal, 56(1), 5–22. doi:10.1002/bimj.201200176

2013

Garding, A., Bhattacharya, N., Haebe, S., Müller, F., Weichenhan, D., Idler, I., et al. (2013). TCL1A and ATM are coexpressed in chronic lymphocytic leukemia cells without deletion of 11q. Haematologica, the hematology journal, 98(2), 269–273. doi:10.3324/haematol.2012.070623

Goeken, N., Ickstadt, K., Bücker-Nott, H.-J., Wilhelm, M., & Hölzer, J. (2013). Untersuchungen zur Auswirkung erhöhter Expositionen gegenüber perfluorierten Verbindungen im Trinkwasser auf die menschliche Gesundheit: eine räumliche Analyse geburtshilflicher Daten in NRW. Das Gesundheitswesen, 75, P65. doi:10.1055/s-0033-1337596

Goeken, N., Ickstadt, K., Schäfer, M., Bücker-Nott, H.-J., Wilhelm, M., & Hölzer, J. (2013a). Untersuchungen zur Auswirkung erhöhter Expositionen gegenüber perfluorierten Verbindungen im Trinkwasser auf die menschliche Gesundheit - eine räumliche Analyse geburtshilflicher Daten in NRW. In GMDS 2013: Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS) ; Lübeck, 01.-05.09.2013. doi:10.3205/13gmds222

Goeken, N., Ickstadt, K., Schäfer, M., Bücker-Nott, H.-J., Wilhelm, M., & Hölzer, J. (2013b). Untersuchungen zur Auswirkung erhöhter Expositionen gegenüber perfluorierten Verbindungen im Trinkwasser auf die menschliche Gesundheit: eine räumliche Analyse geburtshilflicher Daten in NRW. In H. Handels & J. Ingenerf (Eds.), Im Focus das Leben: interdisziplinäre Forschung für die Patientenversorgung der Zukunft ; 01. bis 05. September 2013, Lübeck.

Goeken, N., Ickstadt, K., Schäfer, M., Bücker-Nott, H.-J., Wilhelm, M., & Hölzer, J. (2013c). Statistical approaches to evaluating the association between mother’s exposure to perfluoroalkyl substances (PFASs) and birth outcome in North-Rhine Westphalia. In Abstracts of the 2013 Conference of the International Society of Environmental Epidemiology (ISEE), the International Society of Exposure Science (ISES), and the International Society of Indoor Air Quality and Climate (ISIAQ). https://ehp.niehs.nih.gov/isee/p-2-14-01/

Golka, K., Ickstadt, K., Selinski, S., Hengstler, J. G., & Wilhelm, M. (2013). Second symposium on Environmental Toxicology in North Rhine-Westphalia, Germany-interdisciplinary research activities in toxicology, statistics, hygiene and medicine: meeting report on a symposium held in Dortmund May 19-20, 2011. Archives of toxicology, 87(3), 555–561. doi:10.1007/s00204-013-1014-8

Ickstadt, K. (2013). Bioabundance: ecological statistics. In A. H. El-Shaarawi & W. W. Piegorsch (Eds.), Encyclopedia of environmetrics. doi:10.1002/9780470057339.vab013.pub2

Selinski, S., Blaszkewicz, M., Ickstadt, K., Hengstler, J. G., & Golka, K. (2013). Refinement of the prediction of N-acetyltransferase 2 (NAT2) phenotypes with respect to enzyme activity and urinary bladder cancer risk. Archives of toxicology, 87(12), 2129–2139. doi:10.1007/s00204-013-1157-7

2012

Binder, H., Müller, T., Schwender, H., Golka, K., Steffens, M., Hengstler, J. G., et al. (2012). Cluster-localized sparse logistic regression for SNP data. Statistical applications in genetics and molecular biology, 11(4), 13_1–13_31. doi:10.1515/1544-6115.1694

Flenker, U., Geppert, L. N., & Ickstadt, K. (2012). Validity of stable isotope data in doping control: perspectives and proposals. Drug testing and analysis, 4(12), 934–941. doi:10.1002/dta.1398

Freis, E., Selinski, S., Hengstler, J. G., & Ickstadt, K. (2012). Cluster analytic strategy for identification of metagenes relevant for prognosis of node negative breast cancer. In W. A. Gaul, A. Geyer-Schulz, L. Schmidt-Thieme, & J. Kunze (Eds.), Challenges at the interface of data analysis, computer science, and optimization: proceedings of the 34th Anual Conference of the Gesellschaft für Klassifikation e.V., Karlsruhe, July 21 - 23, 2010 (pp. 475–483). doi:10.1007/978-3-642-24466-7_48

Golka, K., Ickstadt, K., Selinski, S., Hengstler, J. G., & Wilhelm, M. (2012a). Second symposium on interdisciplinary activities in environmental toxicology in North Rhine-Westphalia, Germany. Journal of toxicology and environmental health / A, 75(8-10), 413. doi:10.1080/15287394.2012.674904

Golka, K., Ickstadt, K., Selinski, S., Hengstler, J. G., & Wilhelm, M. (2012b). Second symposium on interdisciplinary activities in environmental toxicology in North Rhine-Westphalia, Germany: part two. Journal of toxicology and environmental health / A, 75(19-20), 1175. doi:10.1080/15287394.2012.707601

Ickstadt, K. (2012). Bioabundance: ecological statistics. In A. H. El-Shaarawi & W. W. Piegorsch (Eds.), Encyclopedia of environmetrics: Band 1, Abi-Con (Vol. 1, pp. 210–212).

Lohr, M., Köllmann, C., Freis, E., Hellwig, B., Hengstler, J. G., Ickstadt, K., & Rahnenführer, J. (2012). Optimal strategies for sequential validation of significant features from high-dimensional genomic data. Journal of toxicology and environmental health / A, 75(8-10), 447–460. doi:10.1080/15287394.2012.674912

Schäfer, M., Lkhagvasuren, O., Klein, H.-U., Elling, C., Wüstefeld, T., Müller-Tidow, C., et al. (2012). Integrative analyses for omics data: a Bayesian mixture model to assess the concordance of ChIP-chip and ChIP-seq measurements. Journal of toxicology and environmental health / A, 75(8-10), 461–470. doi:10.1080/15287394.2012.674914

Schwender, H., Selinski, S., Blaszkewicz, M., Marchan, R., Ickstadt, K., Golka, K., & Hengstler, J. G. (2012). Distinct SNP combinations confer susceptibility to urinary bladder cancer in smokers and non-smokers. PLoS one, 7(12), e51880_1–e51880_12. doi:10.1371/journal.pone.0051880

Selinski, S., Lehmann, M.-L., Blaszkewicz, M., Ovsiannikov, D., Moormann, O., Guballa, C., et al. (2012). Rs11892031[A] on chromosome 2q37 in an intronic region of the UGT1A locus is associated with urinary bladder cancer risk. Archives of toxicology, 86(9), 1369–1378. doi:10.1007/s00204-012-0854-y

2011

Duydu, Y., Başaran, N., Üstündağ, A., Aydın, S., Ündeğer, Ü., Ataman, O. Y., et al. (2011). Reproductive toxicity parameters and biological monitoring in occupationally and environmentally boron-exposed persons in Bandırma, Turkey. Archives of toxicology, 85(6), 589–600. doi:10.1007/s00204-011-0692-3

Golka, K., Selinski, S., Lehmann, M.-L., Blaszkewicz, M., Marchan, R., Ickstadt, K., et al. (2011). Genetic variants in urinary bladder cancer: collective power of the “wimp SNPs.” Archives of toxicology, 85(6), 539–554. doi:10.1007/s00204-011-0676-3

Ickstadt, K., Bornkamp, B., Grzegorczyk, M., Wieczorek, J., Sheriff, M. R., Grecco, H. E., & Zamir, E. (2011). Nonparametric Bayesian networks. In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 9: proceedings of the Ninth Valencia International Meeting; June 3 - 8, 2010 (pp. 283–316). doi:10.1093/acprof:oso/9780199694587.003.0010

Pesch, B., Nasterlack, M., Eberle, F., Bonberg, N., Taeger, D., Leng, G., et al. (2011). The role of haematuria in bladder cancer screening among men with former occupational exposure to aromatic amines. BJU international, 108(4), 1–7. doi:10.1111/j.1464-410X.2010.09971.x

Schmidt, M., Petry, I. B., Böhm, D., Lebrecht, A., von Törne, C., Gebhard, S., et al. (2011). Ep-CAM RNA expression predicts metastasis-free survival in three cohorts of untreated node negative breast cancer. Breast cancer research and treatment, 125(3), 637–646. doi:10.1007/s10549-010-0856-5

Schwender, H., Ruczinski, I., & Ickstadt, K. (2011). Testing SNPs and sets of SNPs for importance in association studies. Biostatistics, 12(1), 18–32. doi:10.1093/biostatistics/kxq042

Selinski, S., Blaszkewicz, M., Lehmann, M.-L., Ovsiannikov, D., Moormann, O., Guballa, C., et al. (2011). Genotyping NAT2 with only two SNPs (rs1041983 and rs1801280) outperforms the tagging SNP rs1495741 and is equivalent to the conventional 7-SNP NAT2 genotype. Pharmacogenetics and genomics, 21(10), 673–678. doi:10.1097/FPC.0b013e3283493a23

Springer, T., Ickstadt, K., & Stöckler, J. (2011). Frame potential minimization for clustering short time series. Advances in data analysis and classification, 5(4), 341–355. doi:10.1007/s11634-011-0097-4

2010

Bornkamp, B., Ickstadt, K., & Dunson, D. (2010). Stochastically ordered multiple regression. Biostatistics, 11(3), 419–431. doi:10.1093/biostatistics/kxq001

Cadenas, C., Franckenstein, D., Schmidt, M., Gehrmann, M. C., Hermes, M., Geppert, B., et al. (2010). Role of thioredoxin reductase 1 and thioredoxin interacting protein in prognosis of breast cancer. Breast cancer research, 12(3), R44_1–R44_15. doi:10.1186/bcr2599

Kracker, H., Bornkamp, B., Kuhnt, S., Gather, U., & Ickstadt, K. (2010). Uncertainty in Gaussian process interpolation. In L. Devroye, B. Karasözen, M. Kohler, & R. Korn (Eds.), Recent developments in applied probability and statistics: dedicated to the memory of Jürgen Lehn; invited papers that were presented at the Workshop on Recent Developments in Applied Probability and Statistics Dedicated to the Memory of Professor Jürgen Lehn, Middle East Technical University (METU), Ankara, April 23 - 24, 2009 (pp. 79–102).

Müller, T., Schiffner, J., Schwender, H., Szepannek, G., Weihs, C., & Ickstadt, K. (2010). Local analysis of SNP data. In H. Locarek-Junge & C. Weihs (Eds.), Classification as a tool for research: proceedings of the 11th IFCS Biennial Conference and 33rd Annual Conference of the Gesellschaft für Klassifikation e.V., Dresden, March 13-18, 2009 (pp. 473–480).

Petry, I. B., Fieber, E., Schmidt, M., Gehrmann, M. C., Gebhard, S., Hermes, M., et al. (2010). ERBB2 induces an antiapoptotic expression pattern of Bcl-2 family members in node-negative breast cancer. Clinical cancer research, 16(2), 451–460.

2009

Bornkamp, B., Fritsch, A., Kuss, O., & Ickstadt, K. (2009). Penalty specialists among goalkeepers: a nonparametric Bayesian analysis of 44 years of German Bundesliga. In B. Schipp & W. Krämer (Eds.), Statistical inference, econometric analysis and matrix algebra: festschrift in honour of Götz Trenkler (pp. 63–76).

Bornkamp, B., & Ickstadt, K. (2009a). Bayesian nonparametric estimation of continuous monotone functions with applications to dose-response analysis. Biometrics, 65(1), 198–205. doi:10.1111/j.1541-0420.2008.01060.x

Bornkamp, B., & Ickstadt, K. (2009b). A note on B-splines for semiparametric elicitation. The American statistician, 63(4), 373–377. doi:10.1198/tast.2009.08191

Freis, E., Selinski, S., Weibert, B., Krahn, U., Schmidt, M., Gehrmann, M. C., et al. (2009). Effects of metagene calculation on survival: an integrative approach using cluster and promoter analysis. In T. Manninen, C. Wiuf, H. Lähdesmäki, M. Grzegorczyk, J. Rahnenführer, M. Ahdesmäki, et al. (Eds.), Sixth International Workshop on Computational Systems Biology (WCSB 2009): June 10 - 12, 2009, Aarhus, Denmark (pp. 47–50).

Fritsch, A., & Ickstadt, K. (2009). Improved criteria for clustering based on the posterior similarity matrix. Bayesian analysis, 4(2), 367–392. doi:10.1214/09-BA414

Golka, K., Hermes, M., Selinski, S., Blaszkewicz, M., Bolt, H. M., Roth, G., et al. (2009). Susceptibility to urinary bladder cancer: relevance of rs9642880[T], GSTM1 0/0 and occupational exposure. Pharmacogenetics and genomics, 19(11), 903–906. doi:10.1097/FPC.0b013e328331b554

Podwojski, K., Fritsch, A., Chamrad, D., Paul, W. J., Sitek, B., Stühler, K., et al. (2009). Retention time alignment algorithms for LC/MS data must consider non-linear shifts. Bioinformatics, 25(6), 758–764.

Schäfer, M., Schwender, H., Merk, S., Haferlach, C., Ickstadt, K., & Dugas, M. (2009). Integrated analysis of copy number alterations and gene expression: a bivariate assessment of equally directed abnormalities. Bioinformatics, 25(24), 3228–3235. doi:10.1093/bioinformatics/btp592

2008

Binner, C., Selinski, S., Barysch, M. J., Pölcher, C., Schormann, W., Hermes, M., et al. (2008). Munich Oktoberfest experience: remarkable impact of sex and age in ethanol intoxication. Archives of toxicology, 82(12), 933–939. doi:10.1007/s00204-008-0373-z

Daumer, M., Held, U., Ickstadt, K., Heinz, M., Schach, S., & Ebers, G. (2008). Reducing the probability of false positive research findings by pre-publication validation: experience with a large multiple sclerosis database. BMC medical research methodology, 8, 18_1–18_7. doi:10.1186/1471-2288-8-18

Harth, V., Schäfer, M., Abel, J., Maintz, L., Neuhaus, T., Besuden, M., et al. (2008). Head and neck squamous-cell cancer and its association with polymorphic enzymes of xenobiotic metabolism and repair. Journal of toxicology and environmental health / A, 71(13-14), 887–897. doi:10.1080/15287390801988160

Ickstadt, K., Schäfer, M., Fritsch, A., Schwender, H., Abel, J., Bolt, H. M., et al. (2008). Statistical methods for detecting genetic interactions: a head and neck squamous-cell cancer study. Journal of toxicology and environmental health / A, 71(11-12), 803–815. doi:10.1080/15287390801985745

Justenhoven, C., Hamann, U., Schubert, F., Zapatka, M., Pierl, C. B., Rabstein, S., et al. (2008). Breast cancer: a candidate gene approach across the estrogen metabolic pathway. Breast cancer research and treatment, 108(1), 137–149. doi:10.1007/s10549-007-9586-8

Müller, T., Schwender, H., & Ickstadt, K. (2008). Finding SNP interactions. In M. Ahdesmäki, K. Strimmer, N. Radde, J. Rahnenführer, K. Klemm, H. Lähdesmäki, & O. Yli-Harja (Eds.), Fifth International Workshop on Computational Systems Biology: WCSB 2008; June 11-13, 2008 Leipzig, Germany; proceedings (pp. 109–112).

Podwojski, K., Fritsch, A., Chamrad, D. C., Paul, W., Mutzel, P., Ickstadt, K., & Rahnenführer, J. (2008). A retention time alignment algorithm for LC/MS data. In M. Ahdesmäki, K. Strimmer, N. Radde, J. Rahnenführer, K. Klemm, H. Lähdesmäki, & O. Yli-Harja (Eds.), Fifth International Workshop on Computational Systems Biology: WCSB 2008; June 11-13, 2008 Leipzig, Germany; proceedings (pp. 129–132).

Schwender, H., & Ickstadt, K. (2008a). Empirical Bayes analysis of single nucleotide polymorphisms. BMC bioinformatics, 9, 144_1–144_15. doi:10.1186/1471-2105-9-144

Schwender, H., & Ickstadt, K. (2008b). Identification of SNP interactions using logic regression. Biostatistics, 9(1), 187–198. doi:10.1093/biostatistics/kxm024

Schwender, H., Ickstadt, K., & Rahnenführer, J. (2008). Classification with high-dimensional genetic data: assigning patients and genetic features to known classes. Biometrical journal, 50(6), 911–926.

Selinski, S., & Ickstadt, K. (2008). Cluster analysis of genetic and epidemiological data in molecular epidemiology. Journal of toxicology and environmental health / A, 71(11-12), 835–844. doi:10.1080/15287390801985828

Taeger, D., Krahn, U., Wiethege, T., Ickstadt, K., Johnen, G., Eisenmenger, A., Wesch, H., Pesch, B., et al. (2008). A study on lung cancer mortality related to radon, quartz, and arsenic exposures in German uranium miners. Journal of toxicology and environmental health / A, 71(13-14), 859–865. doi:10.1080/15287390801987972

Taeger, D., Krahn, U., Wiethege, T., Ickstadt, K., Johnen, G., Eisenmenger, A., Wesch, H., Brüning, T., et al. (2008). Lungenkrebsrisiko von deutschen Uranbergarbeitern durch berufliche Exposition gegenüber Radon, Quarz und Arsen. Arbeitsmedizin, Sozialmedizin, Umweltmedizin, 43, 143.

2007

Fritsch, A., & Ickstadt, K. (2007). Comparing logic regression based methods for identifying SNP interactions. In S. Hochreiter & R. Wagner (Eds.), Bioinformatics research and development: first international conference, BIRD 2007, Berlin, Germany, March 12-14, 2007; proceedings (pp. 90–103). doi:10.1007/978-3-540-71233-6_8

Nunkesser, R., Bernholt, T., Schwender, H., Ickstadt, K., & Wegener, I. (2007). Detecting high-order interactions of single nucleotide polymorphisms using genetic programming. Bioinformatics, 23(24), 3280–3288. doi:10.1093/bioinformatics/btm522

Sturtz, S., & Ickstadt, K. (2007). A descriptive and model-based spatial comparison of the standardised mortality ratio and the age-standardised mortality rate. Geospatial health, 1(2), 255–266. doi:10.4081/gh.2007.273

Taeger, D., Krahn, U., Wiethege, T., Ickstadt, K., Johnen, G., Eisenmenger, A., et al. (2007a). Risk of lung cancer related to radon, quartz ans arsenic exposures in German uranium miners. Symposium on Epidemiology in Occupational Health: Proceedings, 19, 15.

Taeger, D., Krahn, U., Wiethege, T., Ickstadt, K., Johnen, G., Eisenmenger, A., et al. (2007b). Risk of lung cancer related to radon, quartz ans arsenic exposures in German uranium miners. Bochum. http://www.ipa.ruhr-uni-bochum.de/image/poster/229.pdf

2006

Ickstadt, K., Müller, T., & Schwender, H. (2006). Analyzing SNPs: are there needles in the haystack? Chance, 19(3), 21–26. doi:10.1080/09332480.2006.10722798

Schwender, H., Krause, A., & Ickstadt, K. (2006). Identifying interesting genes with siggenes. R News, 6(5), 45–50. https://cran.r-project.org/doc/Rnews/Rnews_2006-5.pdf

Schwender, H., Rabstein, S., & Ickstadt, K. (2006). Do you speak genomish? Chance, 19(3), 3–8. doi:10.1080/09332480.2006.10722794

Spickenheuer, A., van Treeck, U., Schürmann, C., Sturtz, S., & Ickstadt, K. (2006). Anwendung des SSVS-Verfahrens zur Modellfindung am Beispiel der zeitlichen Modellierung von Meldefällen der Campylo-bacteriose. Deutsche Gesellschaft für Epidemiologie: Abstracts, 1, 18.

2004

Schwender, H., Zucknick, M., Ickstadt, K., & Bolt, H. M. (2004). A pilot study on the application of statistical classification procedures to molecular epidemiological data. Toxicology letters, 151(1), 291–299. doi:10.1016/j.toxlet.2004.02.021

Wolpert, R. L., & Ickstadt, K. (2004). Reflecting uncertainty in inverse problems: a Bayesian solution using Lévy processes. Inverse problems, 20(6), 1759–1771. doi:10.1088/0266-5611/20/6/004

2003

Wolpert, R. L., Ickstadt, K., & Hansen, M. B. (2003). A nonparametric Bayesian approach to inverse problems. In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 7: proceedings of the Seventh Valencia International Meeting; dedicated to Dennis V. Lindley; June 2 - 6, 2002 (pp. 403–417). http://ftp.stat.duke.edu/WorkingPapers/02-11.pdf

2002

Best, N. G., Ickstadt, K., Wolpert, R. L., Cockings, S., Elliott, P., Benett, J., et al. (2002). Modeling the impact of traffic-related air pollution on childhood respiratory illness. In C. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiri, A. Gelman, I. Verdinelli, & M. West (Eds.), Case studies in Bayesian statistics: volume V; the 5th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University campus on September 24 - 25, 1999 (Vol. 5, pp. 183–259). doi:10.1007/978-1-4613-0035-9_3

Ickstadt, K. (2002). Bioabundance: ecological statistics. In A. H. El-Shaarawi & W. W. Piegorsch (Eds.), Encyclopedia of environmetrics: Band 1, A - D (Vol. 1, pp. 177–179).

2001

Best, N. G., Ickstadt, K., Wolpert, R. L., & Briggs, D. J. (2001). Combining models of health and exposure data: the SAVIAH study. In P. Elliott, J. Wakefield, N. G. Best, & D. J. Briggs (Eds.), Spatial epidemiology: methods and applications (pp. 393–414).

Ickstadt, K. (2001). On hierarchical point process models in spatial statistics, Habilitation, Fachbereich Mathematik, Technische Universität Darmstadt.

2000

Best, N. G., Ickstadt, K., & Wolpert, R. L. (2000). Spatial Poisson regression for health and exposure data measured at disparate resolutions. Journal of the American Statistical Association, 95(452), 1076–1088. doi:10.2307/2669744

1999

Best, N. G., Ickstadt, K., & Wolpert, R. L. (1999). Bayesian analysis of agricultural field experiments: discussion on the paper by [Julian] Besag and [David] Higdon; [Diskussionsbeitrag]. Journal of the Royal Statistical Society / B, 61(4), 728–729. doi:10.1111/1467-9868.00201/epdf

Ickstadt, K., & Wolpert, R. L. (1999). Spatial regression for marked point processes. In J. M. Bernardo, J. O. Berger, A. P. Dawid, & A. F. M. Smith (Eds.), Bayesian statistics 6: proceedings of the Sixth Valencia International Meeting, June 6 - 10, 1998 (pp. 323–341). http://ftp.stat.duke.edu/WorkingPapers/98-22.pdf

1998

Ickstadt, K., Wolpert, R. L., & Lu, X. (1998). Modeling travel demand in Portland, Oregon. In D. Dey, P. Müller, & D. Sinha (Eds.), Practical nonparametric and semiparametric Bayesian statistics (pp. 305–322). doi:10.1007/978-1-4612-1732-9_17

Wolpert, R. L., & Ickstadt, K. (1998a). Poisson/gamma random field models for spatial statistics. Biometrika, 85(2), 251–267. doi:10.1093/biomet/85.2.251

Wolpert, R. L., & Ickstadt, K. (1998b). Simulation of Lévy random fields. In D. Dey, P. Müller, & D. Sinha (Eds.), Practical nonparametric and semiparametric Bayesian statistics (pp. 227–242). doi:10.1007/978-1-4612-1732-9_12

1997

Ickstadt, K., & Wolpert, R. L. (1997). Multiresolution assessment of forest inhomogeneity. In C. Gatsonis, J. S. Hodges, R. E. Kass, R. McCulloch, P. Rossi, & N. D. Singpurwalla (Eds.), Case studies in Bayesian statistics: volume 3; papers were presented and discussed at a workshop at Carnegie Mellon University, October 5 - 7, 1995 (Vol. 3, pp. 371–385). doi:10.1007/978-1-4612-2290-3_10

1996

Ickstadt, K. (1996). Local sensitivity analysis in Bayesian decision theory: discussion. In J. O. Berger, B. Betrò, E. Moreno, L. R. Pericchi, F. Ruggeri, G. Slinetti, & L. Wasserman (Eds.), Bayesian robustness: proceedings of the Workshop on Bayesian Robustness, May 22-May 25, 1995, Rimini, Italy (pp. 133–134). http://www.jstor.org/stable/4355914

Ickstadt, K., Jin, S., & Polasek, W. (1996). Metropolis sampling in bilinear time series models. In H.-H. Bock & W. Polasek (Eds.), Data analysis and information systems: statistical and conceptual approaches; , University of Basel, March 8 – 10, 1995 (pp. 313–323). doi:10.1007/978-3-642-80098-6_26

1995

Ritter, M., Biber-Klemm, S., Ickstadt, K., Kocher-Schmid, C., & Stettler, N. (1995). Gesellschaftliche Wahrnehmung, Bewertung und Umsetzung von Biodiversität. Gaia, 4(4), 250–260.

1994

Eichenauer-Herrmann, J., & Ickstadt, K. (1994). Explicit inversive congruential pseudorandom numbers with power of two modulus. Mathematics of computation, 62(206), 787–797. doi:10.2307/2153539

Eichenauer-Herrmann, J., Ickstadt, K., & Weiß, E. (1994). Gamma-minimax results for the class of unimodal priors. Statistical papers, 35(1), 43–56. doi:10.1007/BF02926399

Ickstadt, K. (1994). Multivariate Parameterschätzung bei Klassen von verallgemeinerten unimodalen a priori Verteilungen, Dissertation, Fachbereich Mathematik, Technische Universität Darmstadt.

1993

Eichenauer-Herrmann, J., & Ickstadt, K. (1993). A saddle point characterization for classes of priors with shape-restricted densities. Statistics & decisions, 11, 175–179. doi:10.1524/strm.1993.11.2.175

Ickstadt, K. (1993). Existence and characterization of saddle points in statistical games for classes of generalized unimodal priors. In Conference proceedings, 8-th European Young Statisticians Meeting: Palanga, September 5 - 12, 1993 (pp. 51–55).

1992

Eichenauer-Herrmann, J., & Ickstadt, K. (1992). Minimax estimators for a bounded location parameter. Metrika, 39(1), 227–237. doi:10.1007/BF02614006

Ickstadt, K. (1992). Gamma-minimax estimators with respect to unimodal priors. In P. Gritzmann, R. Hettich, R. Horst, & E. Sachs (Eds.), Operations research ’91: extended abstracts of the 16th Symposium on Operations Research held at the University of Trier at September 9–11, 1991 (pp. 330–333).

Buchbesprechungen

  • Ickstadt, K. (2003). Besprechung des Buches von Chen, M.-H., Shao, Q.-M. and Ibrahim, J.G.: Monte Carlo Methods in Bayesian Computations, Springer-Verlag, in Metrika 57, 97-98.  
  • Ickstadt, K. (2001). Diskussion des Buches von Lawson, A., Biggeri, A., Böhning, D., Lesaffre, E., Viel, J.-F. und Bertollini, R.: Disease Mapping and Risk Assessment for Public Health, John Wiley & Sons, in Statistics in Medicine 20, 983-984.
  • Ickstadt, K. (2000). Diskussion des Buches von Müller, W.G. (1998): Collecting Spatial Data, Physica-Verlag, in Computational Statistics 15, 313-314.

Ausgewählte Technical Reports

  • Müller, T., Selinski, S. und Ickstadt, K. (2005), Cluster Analysis: A comparison of different similarity measures for SNP data, Technical Report 14/2005, SFB 475, Universität Dortmund.
  • Schwender, H., Krause, A. und Ickstadt, K. (2003). Comparison of the empirical Bayes and the significance analysis of Microarrays, Technical Report 44/2003, SFB 475, Universität Dortmund.
  • Selinski, S. und Ickstadt, K. (2005), Similarity measures for clustering SNP data, Technical Report 27/2005, SFB 475, Universität Dortmund.

Sonstige Arbeiten

  • Ickstadt, K. (2001). On hierarchical point process models in spatial statistics, Habilitation, Fachbereich Mathematik, Technische Universität Darmstadt.
  • Ickstadt, K. (1994). Multivariate Parameterschätzung bei Klassen von verallgemeinerten unimodalen a priori Verteilungen, Dissertation, Fachbereich Mathematik, Technische Universität Darmstadt.

Anfahrt & Lageplan

Der Campus der Technischen Universität Dortmund liegt in der Nähe des Autobahnkreuzes Dortmund West, wo die Sauerlandlinie A45 den Ruhrschnellweg B1/A40 kreuzt. Die Abfahrt Dortmund-Eichlinghofen auf der A45 führt zum Campus Süd, die Abfahrt Dortmund-Dorstfeld auf der A40 zum Campus-Nord. An beiden Ausfahrten ist die Universität ausgeschildert.

Direkt auf dem Campus Nord befindet sich die S-Bahn-Station „Dortmund Universität“. Von dort fährt die S-Bahn-Linie S1 im 15- oder 30-Minuten-Takt zum Hauptbahnhof Dortmund und in der Gegenrichtung zum Hauptbahnhof Düsseldorf über Bochum, Essen und Duisburg. Außerdem ist die Universität mit den Buslinien 445, 447 und 462 zu erreichen. Eine Fahrplanauskunft findet sich auf der Homepage des Verkehrsverbundes Rhein-Ruhr, außerdem bieten die DSW21 einen interaktiven Liniennetzplan an.
 

Zu den Wahrzeichen der TU Dortmund gehört die H-Bahn. Linie 1 verkehrt im 10-Minuten-Takt zwischen Dortmund Eichlinghofen und dem Technologiezentrum über Campus Süd und Dortmund Universität S, Linie 2 pendelt im 5-Minuten-Takt zwischen Campus Nord und Campus Süd. Diese Strecke legt sie in zwei Minuten zurück.

Vom Flughafen Dortmund aus gelangt man mit dem AirportExpress innerhalb von gut 20 Minuten zum Dortmunder Hauptbahnhof und von dort mit der S-Bahn zur Universität. Ein größeres Angebot an internationalen Flugverbindungen bietet der etwa 60 Kilometer entfernte Flughafen Düsseldorf, der direkt mit der S-Bahn vom Bahnhof der Universität zu erreichen ist.