Vieland, Veronica J (2016) Measurement of Statistical Evidence: Picking Up Where Hacking (et al.) Left Off. In: UNSPECIFIED.

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Abstract

Hacking’s (1965) Law of Likelihood says – paraphrasing– that data support hypothesis H1 over hypothesis H2 whenever the likelihood ratio (LR) for H1 over H2 exceeds 1. But Hacking (1972) noted a seemingly fatal flaw in the LR itself: it cannot be interpreted as the degree of “evidential significance” across applications. I agree with Hacking about the problem, but I don’t believe the condition is incurable. I argue here that the LR can be properly calibrated with respect to the underlying evidence, and I sketch the rudiments of a methodology for so doing.

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Item Type:	Conference or Workshop Item (UNSPECIFIED)
Creators:	Creators Email ORCID Vieland, Veronica J veronica.vieland@nationwidechildrens.org
Keywords:	statistics, statistical evidence, likelihood ratio, measurement
Subjects:	Specific Sciences > Biology General Issues > Confirmation/Induction Specific Sciences > Probability/Statistics
Depositing User:	VJ Vieland
Date Deposited:	26 Oct 2016 12:47
Last Modified:	26 Oct 2016 12:47
Item ID:	12515
Subjects:	Specific Sciences > Biology General Issues > Confirmation/Induction Specific Sciences > Probability/Statistics
Date:	November 2016
URI:	https://philsci-archive.pitt.edu/id/eprint/12515

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