No evidence amalgamation without evidence measurement

Synthese 196 (8):3139-3161 (2019)
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In this paper we consider the problem of how to measure the strength of statistical evidence from the perspective of evidence amalgamation operations. We begin with a fundamental measurement amalgamation principle : for any measurement, the inputs and outputs of an amalgamation procedure must be on the same scale, and this scale must have a meaningful interpretation vis a vis the object of measurement. Using the p value as a candidate evidence measure, we examine various commonly used approaches to amalgamation of evidence across similar studies, including standard forms of meta-analysis. We show that none of these methods satisfies MAP. Thus an underlying measurement problem remains. We argue that a successful approach to evidence amalgamation necessitates a solution to the problem of evidence measurement, and we suggest some lines of reasoning that might guide further work towards this end.



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Author Profiles

Veronica J. Vieland
Ohio State University
Hasok Chang
Cambridge University

References found in this work

A Mathematical Theory of Evidence.Glenn Shafer - 1976 - Princeton University Press.
Logic of Statistical Inference.Ian Hacking - 1965 - Cambridge, England: Cambridge University Press.
The book of evidence.Peter Achinstein - 2001 - New York: Oxford University Press.

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