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Comment on “Automated Versus Do-It-Yourself Methods for Causal Inference: Lessons Learned from a Data Analysis Competition”

  • Autores: Susan Gruber, Mark J. van der Laan
  • Localización: Statistical science, ISSN 0883-4237, Vol. 34, Nº. 1, 2019, págs. 82-85
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • Dorie and co-authors (DHSSC) are to be congratulated for initiating the ACIC Data Challenge. Their project engaged the community and accelerated research by providing a level playing field for comparing the performance of a priori specified algorithms. DHSSC identified themes concerning characteristics of the DGP, properties of the estimators, and inference.We discuss these themes in the context of targeted learning.


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