How to Make People Immortal and Why it is Not a Good Idea: Improving the Causal Analyses of Healthcare Databases
Abstract: The generation of “immortal time” is a frequent blunder in survival analyses for causal inference. Immortal time explains why medical treatments often look suspiciously amazing. After two centuries of warnings, immortal time still plagues causal analyses in medicine, which is fascinating because “immortal time” doesn’t exist in the data. Rather, we generate immortal time when analyzing the data incorrectly. This talk summarizes why immortal time arises in survival analyses and how to prevent it.
Bio: Miguel Hernán is the Director of CAUSALab, the Kolokotrones Professor of Biostatistics and Epidemiology at the Harvard T.H. Chan School of Public Health, and faculty at the Harvard-MIT Division of Health Sciences and Technology. He and his collaborators repurpose real world data into evidence for the prevention and treatment of infectious diseases, cancer, cardiovascular disease, and mental illness. This work has contributed to shape health research methodology worldwide.