- Statist. Sci.
- Volume 34, Number 1 (2019), 72-76.
Comment: Will Competition-Winning Methods for Causal Inference Also Succeed in Practice?
First, we would like to congratulate the authors for successfully hosting the causal inference data competition (referred to as Competition henceforth) and contributing a unique and thought-provoking article to the literature. The authors have provided a comprehensive and timely platform to evaluate the ever-growing number of methods used for covariate adjustment in observational studies. In our comment, we don’t generally question the results of the competition, but we do wish to emphasize several other key elements about the role statistics plays in causal inference and observational studies.
Statist. Sci., Volume 34, Number 1 (2019), 72-76.
First available in Project Euclid: 12 April 2019
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Zhao, Qingyuan; Keele, Luke J.; Small, Dylan S. Comment: Will Competition-Winning Methods for Causal Inference Also Succeed in Practice?. Statist. Sci. 34 (2019), no. 1, 72--76. doi:10.1214/18-STS680. https://projecteuclid.org/euclid.ss/1555056032
- Main article: Automated versus Do-It-Yourself Methods for Causal Inference: Lessons Learned from a Data Analysis Competition.