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Retreat
Date and Time: 05.09-06.09.2022
Speaker: Dr. Paul Bürkner , Independent Junior Research Group Leader for Bayesian Statistics, University of Stuttgart
Date and Time: 21.02.-22.02.2022
Date : 23.09.-24.09.2021
Workshop “Joy of P-Splines”
Speaker : Prof. Brian D. Marx , Department of Experimental Statistics Louisiana State University
Date : 05.07-06.07.2021
Random forests on high-dimensional data: from classification and survival analysis to generative modelling
Speaker: Prof. Dr. Marvin N. Wright, Leibniz-Institut für Präventionsforschung und Epidemiologie – BIPS, Bremen
Date and Time: 04.07.2022
Issues in supervised prediction and classification for complex chemical substances
Speaker: Prof. Fred Wright, Ph.D., Departments of Statistics and Biological Sciences, North Carolina State University, USA
Date and Time: 27.06.2022, TU Dortmund, M/E 21
Modeling Heterogeneity for Stratified Populations (Click to see abstract)
We frequently encounter stratified data. In precision medicine, patients are exposed to different treatment options. In health disparities research, race, gender, and rurality are key indicators for investigation. In health care management, health outcomes of elderly patients are greatly influenced by presence of their existing chronic conditions. In this talk, I present some strategies to model such stratified data to address interested research questions from my collaboration with medical investigators. The talk will focus on model building in the presence of many covariates rather than computational and theoretical results, which are available in published works. It will cover stratification by one indicator, by two indicators, by three indicators, and if time permits, by many more multilevel indicators.
Speaker: Prof. Menggang Yu, Department of Biostatistics and Medical informatics, University of Wisconsin-Madison, USA
Date and Time: 24.06.2022 at 12.00, TU Dortmund, M/E 21
Propensity Score: an Alternative Method of Analyzing Intervention Effect. (Click to see abstract)
There is agreement in medical research that the preferred method for evaluating interventions is the randomized controlled trial. Randomization is the only method that guarantees similar distributions of known and unknown patient characteristics between an intervention and a control group thus enabling true causal statements on intervention effects. However, randomized controlled trials are in some cases "unnecessary, inappropriate, impossible, or inadequate" and have also been criticized for a lack of external validity: Patients in randomized controlled trials are usually younger and healthier than the average patient. Non-randomized studies can be an alternative here, however, they suffer from a lack of internal validity: Treatment allocation is not randomized and the intervention and control groups may be systematically different in terms of known and (even worse) unknown patient characteristics. A range of statistical procedures have been developed to take account of these differences during analysis. The standard procedures for this are multiple regression models, however, propensity scores (PS) are also increasingly used. The propensity score is defined as the probability that a patient receives the intervention under investigation. In a first step, the PS is estimated from the available data, e.g. in a logistic regression model. In a second step, the actual intervention effect is estimated with the aid of the PS. In this talk, we give a short, non-technical introduction to the propensity score using an example from coronary bypass surgery.
Speaker: Prof. Dr. sc. hum. Oliver Kuß, Deutsches Diabetes-Zentrum, Düsseldorf
Date and Time: 20.06.2022 via Zoom
Gene expression to Omics: The evolution of genetic research
Speaker: Ashtyn Areal, IUF Düsseldorf
Date and Time: 30.05.2022, TU Dortmund, M/E 21
Analysis and design of clinical trials with biologics using dose-time-response models
Speaker: Markus Lange, Novartis
Date and Time: 23.05.2022 via Zoom
The case time series design for high-dimensional data analyses
Speaker: Prof. Antonio Gasparrini, London School of Hygiene and Tropical Medicine, London, UK
Date and Time: 16.05.2022 via Zoom
Mehrstadien-Modelle in der Epidemiologie chronischen Erkrankungen
Speaker: Prof. Dr. rer. nat. Ralph Brinks , Lehrstuhl für Medizinische Biometrie und Epidemiologie, Private Universität Witten/Herdecke gGmbH
Date and Time: 09.05.2022 at 16:15 via Zoom
Assessing interactive effects of air pollution and temperature– approaches and challenges?
Speaker: Dr. Susanne Breitner , Helmholtz-Zentrum München
Date and Time: 14.02.2022 at 16:15 via Zoom
Speaker: Prof. Dr. Ludwig Hothorn, Biostatistician, Retired from Leibniz University Hannover
Date and Time: 24.01.2022 at 16:15 via Zoom
Speaker: Associate Professor Laura Saba, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, USA
Date and Time: 10.01.2022 at 16:15 via Zoom
Can statistics save preclinical research?
Speaker: Prof. Dr. med. Ulrich Dirnagl, Abteilungsdirektor Experimentelle Neurologie, Charité Berlin
Date and Time: 06.12.2021 at 16:15 via Zoom
Dose-response analysis for gene-expression data (Click to see abstract)
Advances in genomics bring forward increasingly large omics data sets, such that even concentration-resolved gene expression data are available. We transfer well established dose-response theory from clinical research to toxicological gene expression data.
Multiple-Comparison-Procedure and Modeling (MCP-Mod) is a relatively new dose-response modeling technique developed for Phase II clinical dose-finding trials that accounts for model uncertainty. By applying MCP-Mod on a concentration-resolved gene expression data set, we find that commonly assumed monotonicity is not adequate and model uncertainty should be considered.
Speaker: Scott S. Auerbach, PhD, und Matt Wheeler, PHD, Institute of Environmental Health Sciences, Durham, NC, USA
Date and Time: 29.11.2021 at 16:15 via Zoom
Good Scientific Practise for Doctoral Researchers
Speaker: Dr. Peter Schröder, brain4hire, Graduiertenzentrum TU Dortmund
Date and Time: 15.11.2021 at 16:15 via Zoom
Recent extensions on boosting for statistical modelling
Speaker: Prof. Dr. Andreas Mayr, Head of WG Statistical Methods in Epidemiology, Universität Bonn
Date and Time: 25.10.2021 at 16:15 via Zoom
Polygenic risk scores – Applicability beyond risk prediction and for different omics data
Speaker: Anke Hüls, PhD, MSc, Assistant Professor, Department of Epidemiology and Gangarosa Department of Environmental Health, Emory University
Date and Time: 05.08.2021 at 16:15 via Zoom
Advances in dose-response analysis
Speaker: Prof. Christian Ritz , National Institute of Public Health,Copenhagen
Date and Time: 28.06.2021 at 16:15 via Zoom