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Prior Information in Frequentist Study Designs: The Case of Neyman’s Sampling Theory

Kubiak, Adam P. and Kawalec, Paweł (2021) Prior Information in Frequentist Study Designs: The Case of Neyman’s Sampling Theory. [Preprint]

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Abstract

We analyse the issue of using prior information in frequentist statistical inference. For that purpose, we scrutinise different kinds of sampling designs in Jerzy Neyman’s theory to reveal a variety of ways to explicitly and objectively engage with prior information. Further, we turn to the debate on sampling paradigms (design-based vs. model-based approach) to argue that Neyman’s theory provides an argument for the conciliatory approach in the frequentism vs. Bayesianism debate. We also demonstrate that while Neyman’s theory, by allowing non-epistemic values to influence evidence collection and formulation of statistical conclusions, does not compromise the epistemic reliability of the procedures and may improve it. This undermines the value-free ideal of scientific inference.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Kubiak, Adam P.adampkubiak@gmail.com0000-0001-7178-3784
Kawalec, Pawełpawel.kawalec@kul.pl0000-0001-7618-8298
Keywords: frequentism, design-based approach, model-based approach, non-epistemic factors, sampling, Neyman, prior information, value-free ideal of science
Subjects: General Issues > Data
General Issues > Experimentation
General Issues > History of Philosophy of Science
Specific Sciences > Probability/Statistics
General Issues > Values In Science
Depositing User: Adam Kubiak
Date Deposited: 10 Jun 2021 03:40
Last Modified: 10 Jun 2021 03:40
Item ID: 19161
Subjects: General Issues > Data
General Issues > Experimentation
General Issues > History of Philosophy of Science
Specific Sciences > Probability/Statistics
General Issues > Values In Science
Date: 6 June 2021
URI: http://philsci-archive.pitt.edu/id/eprint/19161

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