معرفی
Theis Lange is a Professor of Biostatistics and Head of the Department of Public Health at the University of Copenhagen's Faculty of Health and Medical Sciences. His work bridges methodological statistics with diverse medical applications, collaborating extensively with medical doctors, epidemiologists, and psychologists across various clinical domains.
Dr. Lange earned his Ph.D. in Mathematical Statistics from the University of Copenhagen in 2008, following earlier degrees including an M.Sc. in Mathematics and Economics from the same institution and an M.Sc. in Econometrics from the London School of Economics. His academic journey progressed from Assistant Professor (2009-2021) to his current dual role as Professor and Department Head since 2021.
His research focuses primarily on causal inference methodology and its application across medical domains. His work spans from randomized controlled trials to complex longitudinal observational studies, with applications ranging from intensive care to psychology. His methodological innovations in causal inference earned him the 2012 Kenneth Rothman Prize. Recent work demonstrates his expertise in clinical trial design, vaccine development methodology, and advanced statistical approaches for real-world evidence generation.
His publication portfolio shows a strong emphasis on methodological development applied to pressing medical questions. Recent articles reveal expertise in genetic epidemiology, cardiovascular research, diabetes complications, cancer outcomes, and digital health implementation. His work consistently applies sophisticated causal inference techniques to address confounding and bias in observational studies.
Among his notable achievements is the 2012 Kenneth Rothman Prize recognizing his methodological contributions to causal inference. He serves on the board of Fonden for Mental Sundhed and has participated in Data Safety Monitoring Committees for pharmaceutical companies including Novo Nordisk and Leo Pharma.
Dr. Lange has extensive experience reviewing for top statistical and medical journals including Biometrics, Journal of Business and Economic Statistics, Statistics in Medicine, and The New England Journal of Medicine. His technical expertise includes programming in C++, Ox, and R, along with statistical packages SPSS, SAS, and GiveWin.
