On objectivity and subjectivity in statistical inference: A response to Mayo
Synthese 67 (2):369 - 379 (1986)
| Abstract | In this paper we respond to the article An Objective Theory of Statistical Testing by D. G. Mayo (1983). We argue that the theory of testing developed by Mayo, NPT*, is neither novel nor objective. We also respond to the claims made by Mayo against Bayesian theory. | |||||||||
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Colin Howson (1997). Error Probabilities in Error. Philosophy of Science 64 (4):194.
Deborah G. Mayo (1997). Error Statistics and Learning From Error: Making a Virtue of Necessity. Philosophy of Science 64 (4):212.
Gregory Wheeler (2000). Error Statistics and Duhem's Problem. Philosophy of Science 67 (3):410-420.
Thomas Bartz-Beielstein (2008). How Experimental Algorithmics Can Benefit From Mayo's Extensions to Neyman–Pearson Theory of Testing. Synthese 163 (3):385 - 396.
Wendy S. Parker (2008). Computer Simulation Through an Error-Statistical Lens. Synthese 163 (3):371 - 384.
David Wÿss Rudge (2001). Kettlewell From an Error Statisticians's Point of View. Perspectives on Science 9 (1):59-77.
Andrés Rivadulla (1991). Mathematical Statistics and Metastatistical Analysis. Erkenntnis 34 (2):211 - 236.
Kent Staley (2012). Strategies for Securing Evidence Through Model Criticism. European Journal for Philosophy of Science 2 (1):21-43.
Deborah G. Mayo (1983). An Objective Theory of Statistical Testing. Synthese 57 (3):297 - 340.
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