Lecture by Professor John P.A. Ioannidis
Reproducibility challenges towards improving the evidence base for modern science
The lecture will overview the current status on research on reproducibility across diverse scientific fields. Reproducibility of methods, results, and inferences will be discussed. Empirical data suggest that there is less than optimal reproducibility in many scientific fields. This poses challenges in trusting and building upon the accumulated evidence. Solutions for improving reproducibility and credible evidence will be discussed. John P.A. Ioannidis is C.F. Rehnborg Chair in Disease Prevention at Stanford University, Professor of Medicine, Professor of Health Research and Policy, Professor (by courtesy) of Biomedical Data Science at the School of Medicine and Professor of Statistics (by courtesy) at the School of Humanities and Sciences. He is also co-Director, Meta-Research Innovation Center at Stanford (METRICS).
Host: Carl Johan Sundberg, Chair, Department of Learning, Informatics, Management and Ethics and Professor at Department of Physiology & Pharmacology.
Publications, see https://www.ncbi.nlm.nih.gov/pubmed/?term=ioannidis+jp
More information: https://metrics.stanford.edu/