Leo Held

Leo Held admin October 6, 2023

An introduction to
Issues in Reproducibility and Replicability

by LEO HELD
There are increasing concerns about the lack of reproducibility and replicability in biomedical research. The current incentive system prioritizes quantity over quality and innovation over validation, thus encouraging questionable research practices and eventually reducing the reproducibility and generalizability of published findings. In this talk I will discuss current insights on the extent of non-reproducible biomedical research and describe possible strategies to improve research quality.

Mini Bio

Leo Held
FULL PROFESSOR OF BIOSTATISTICS AT THE UNIVERSITY OF ZURICH

Leonhard Held is Full Professor of Biostatistics at the University of Zurich (UZH). He is currently Head of the Biostatistics Department at the Epidemiology, Biostatistics and Prevention Institute, Program Director of the Master Program in Biostatistics and Director of the Center for Reproducible Science at UZH.
Prof. Held obtained his Ph.D. in 1997 at the Department of Statistics at the Ludwig-Maximilians-Universität München (LMU Munich) under the supervision of Ludwig Fahrmeir. During his Ph.D. studies he spent a year at the Department of Statistics of the University of Washington in Seattle, USA. He was Lecturer and Senior Lecturer in Medical Statistics at Imperial College London (2000-2001) and Lancaster University (2001-2002), UK. He then spent four years (2003-2006) at LMU Munich as Associate Professor of Biostatistics. Since September 2006 he is faculty member of the Medical Faculty and the Faculty of Science of the University of Zurich.
Prof. Held was Associate Editor for Biostatistics (2001-2007), Applied Statistics (JRSSC) (2002-2005) and Statistical Modelling(2007-2008). He has served as Associate Editor and Editor of Biometrical Journal from 2008 to 2017. He is currently Editor of the Annals of Applied Statistics for Epidemiology and Clinical Science.
His current methodological research interests are in statistical aspects of reproducibility and replicability, infectious disease data analysis and Bayesian inference. Most of his research is motivated by epidemiological and clinical applications. He is particularly well-known for his contributions to Spatial Epidemiology and Bayesian Biostatistics.