Comment: Spherical cows in a vacuum: data analysis competitions for causal inference.

*(English)*Zbl 1420.62348Summary: A recent data analysis competition compared the performance of several methods for causal inference from observational data. However, sound causal inference requires not only adequate data analysis techniques but also subject-matter expertise about the causal structure of the problem under study. Therefore, until a methodology is developed to combine data analysis and subject-matter knowledge, causal inference competitions may only provide advice to practitioners under ideal conditions.

Comment on [V. Dorie et al., “Automated versus do-it-yourself methods for causal inference: lessons learned from a data analysis competition”, ibid. 34, No. 1, 43–68 (2019; Zbl 1420.62345)].

Comment on [V. Dorie et al., “Automated versus do-it-yourself methods for causal inference: lessons learned from a data analysis competition”, ibid. 34, No. 1, 43–68 (2019; Zbl 1420.62345)].

##### MSC:

62K20 | Response surface designs |

68T05 | Learning and adaptive systems in artificial intelligence |

62B15 | Theory of statistical experiments |

**OpenURL**

##### References:

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