Machine Learning for Causal Inference: On the Use of Cross-fit Estimators.

Journal: Epidemiology (Cambridge, Mass.)
Published Date:

Abstract

BACKGROUND: Modern causal inference methods allow machine learning to be used to weaken parametric modeling assumptions. However, the use of machine learning may result in complications for inference. Doubly robust cross-fit estimators have been proposed to yield better statistical properties.

Authors

  • Paul N Zivich
    From the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC.
  • Alexander Breskin
    NoviSci, Durham, NC.