Strategies for securing evidence through model criticism

Abstract
Some accounts of evidence regard it as an objective relationship holding between data and hypotheses, perhaps mediated by a testing procedure. Mayo’s error-statistical theory of evidence is an example of such an approach. Such a view leaves open the question of when an epistemic agent is justified in drawing an inference from such data to a hypothesis. Using Mayo’s account as an illustration, I propose a framework for addressing the justification question via a relativized notion, which I designate security , meant to conceptualize practices aimed at the justification of inferences from evidence. I then show how the notion of security can be put to use by showing how two quite different theoretical approaches to model criticism in statistics can both be viewed as strategies for securing claims about statistical evidence
Keywords Evidence  Statistics  Robustness  Mis-specification testing  Error-statistics  Justification  Security  Statistical models
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References found in this work BETA
David J. Chalmers (2011). The Nature of Epistemic Space. In Andy Egan & Brian Weatherson (eds.), Epistemic Modality. Oxford University Press.
Keith DeRose (1991). Epistemic Possibilities. Philosophical Review 100 (4):581-605.
Jaakko Hintikka (1962). Knowledge and Belief. Ithaca, N.Y.,Cornell University Press.

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