False Models and Post-Data Model Construction
- 1 March 1974
- journal article
- research article
- Published by JSTOR in Journal of the American Statistical Association
- Vol. 69 (345) , 122
- https://doi.org/10.2307/2285510
Abstract
This article proposes a method of discounting evidence when linear regression models are constructed after the data have been partially analyzed. The solution parallels a formal decision theoretic analysis of a presimplification problem in which models or model spaces are simplified before observation in order to avoid observation or processing costs. Post-data model construction is interpreted as the data-dependent decision that this pre-simplification is undesirable. The discounting implications of this formal analysis may then be used to police data analyses with less formal post-data model construction.Keywords
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