The Future of Causal Inference.

Journal: American journal of epidemiology
PMID:

Abstract

The past several decades have seen exponential growth in causal inference approaches and their applications. In this commentary, we provide our top-10 list of emerging and exciting areas of research in causal inference. These include methods for high-dimensional data and precision medicine, causal machine learning, causal discovery, and others. These methods are not meant to be an exhaustive list; instead, we hope that this list will serve as a springboard for stimulating the development of new research.

Authors

  • Nandita Mitra
    1 Department of Biostatistics & Epidemiology, University of Pennsylvania, Philadelphia, PA, USA.
  • Jason Roy
    Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Piscataway, New Jersey 08854, USA.
  • Dylan Small