- Statist. Sci.
- Volume 34, Number 4 (2019), 584-590.
Comment: Models Are Approximations!
This discussion focuses on areas of disagreement with the papers, particularly the target of inference and the case for using the robust ‘sandwich’ variance estimator in the presence of moderate mis-specification. We also suggest that existing procedures may be appreciably more powerful for detecting mis-specification than the authors’ RAV statistic, and comment on the use of the pairs bootstrap in balanced situations.
Statist. Sci., Volume 34, Number 4 (2019), 584-590.
First available in Project Euclid: 8 January 2020
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Davison, Anthony C.; Koch, Erwan; Koh, Jonathan. Comment: Models Are Approximations!. Statist. Sci. 34 (2019), no. 4, 584--590. doi:10.1214/19-STS746. https://projecteuclid.org/euclid.ss/1578474023
- Main article: Models as Approximations I: Consequences Illustrated with Linear Regression.
- Main article: Models as Approximations II: A Model-Free Theory of Parametric Regression.