Description: Using data from various clinical trials and other studies, methodology and statistical concepts are presented that remain solid also when studies are very small, such as in rare diseases, or very large. In the former case, we need to ensure that the statistical methodology leads to reliable estimates, without being riddled with computational instability. In the latter case, we need to ensure that running times remain feasible. Specific attention is devoted to the potential of surrogate markers and the omnipresent problem of incomplete data. The focus is on concepts and illustration, not on mathematical detail.
Lecturer: Prof. Geert Molenberghs – Hasselt University and KU Leuven, Belgium
GeertMolenberghsis Professor of Biostatistics atUHasselt and KU Leuven. Hereceived a degree in mathematics (1988) and a Ph.D. in biostatistics (1993) from UAntwerpen.He published on surrogate markers in clinical trials,andcategorical, longitudinal, and missing data. Hewas Editor for Applied Statistics, Biometrics,andBiostatistics, andis currently Executive Editor of Biometrics. He was President of the International Biometric Society. Heis Fellow of the American Statistical Association,received the Guy Medal in Bronze from the Royal StatisticalSociety,and held visiting positions at Harvard.He isfounding director of the Center for Statistics atUHasselt and of the Interuniversity Institute for Biostatistics and statistical Bioinformatics (UHasselt and KU Leuven). He received research funding from FWO, IWT, the EU (FP7), U.S. NIH, U.S. NSF,UHasselt, KU Leuven, ECDC, and EMA. He is member of the Belgian Royal Academy of Medicine.He has been active (as advisor, researcher, and communicator) in the SARS-CoV-2 pandemic response. He has taken part in various grant funded research programs on rare diseases, including IDEAL, EJP RD, ERDERA, andRealiseD.