UB Paderborn / Katalog / Suche / in CDI

The statistics wars and intellectual conflicts of interest

Conservation biology, 2022-02, Vol.36 (1), p.e13861-n/a

Mayo, Deborah G.

2022

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P‐value thresholds: Forfeit at your peril

European journal of clinical investigation, 2019-10, Vol.49 (10), p.e13170-n/a

Mayo, Deborah G.

2019

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Statistical significance and its critics: practicing damaging science, or damaging scientific practice?

Synthese (Dordrecht), 2022-06, Vol.200 (3), p.220-220, Article 220

2022

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Significance Tests: Vitiated or Vindicated by the Replication Crisis in Psychology?

Review of philosophy and psychology, 2021-03, Vol.12 (1), p.101-120

Mayo, Deborah G.

2021

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On the Birnbaum Argument for the Strong Likelihood Principle

Statistical science, 2014-05, Vol.29 (2), p.227-239

Mayo, Deborah G.

2014

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Severe Testing as a Basic Concept in a Neyman–Pearson Philosophy of Induction

The British journal for the philosophy of science, 2006-06, Vol.57 (2), p.323-357

2006

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Remembering Sir David Cox, 1924–2022

Significance (Oxford, England), 2022-04, Vol.19 (2), p.30-37

2022

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Error statistical modeling and inference: Where methodology meets ontology

Synthese (Dordrecht), 2015-11, Vol.192 (11), p.3533-3555

2015

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Statistics, philosophy, and health: the SMAC 2021 webconference

The international journal of biostatistics, 2022-12, Vol.19 (2), p.261-270

2022

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Rejoinder: "On the Birnbaum Argument for the Strong Likelihood Principle"

Statistical science, 2014-05, Vol.29 (2), p.261-266

Mayo, Deborah G.

2014

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The error-statistical philosophy and the practice of Bayesian statistics: Comments on Gelman and Shalizi: 'Philosophy and the practice of Bayesian statistics'

British journal of mathematical & statistical psychology, 2013-02, Vol.66 (1), p.57-64

Mayo, Deborah G.

2013

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Ontology & methodology

Synthese (Dordrecht), 2015-11, Vol.192 (11), p.3413-3423

2015

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Methodology in Practice: Statistical Misspecification Testing

Philosophy of science, 2004-12, Vol.71 (5), p.1007-1025

2004

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How to Discount Double-Counting When It Counts: Some Clarifications

The British journal for the philosophy of science, 2008-12, Vol.59 (4), p.857-879

Mayo, Deborah G.

2008

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Five ways to ensure that models serve society: a manifesto

Nature (London), 2020-06, Vol.582 (7813), p.482-484

2020

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Philosophical Scrutiny of Evidence of Risks: From Bioethics to Bioevidence

Philosophy of science, 2006-12, Vol.73 (5), p.803-816

2006

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In Regard to Fornacon-Wood et al

International journal of radiation oncology, biology, physics, 2023-01, Vol.115 (1), p.249-250

2023

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Discussion: Bayesian Methods: Applied? Yes. Philosophical Defense? In Flux

The American statistician, 2013-02, Vol.67 (1), p.11-15

Mayo, Deborah G.

2013

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When Can Risk-Factor Epidemiology Provide Reliable Tests?

Epidemiology (Cambridge, Mass.), 2004-09, Vol.15 (5), p.523-524

2004

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Peircean Induction and the Error-Correcting Thesis

Transactions of the Charles S. Peirce Society, 2005-04, Vol.41 (2), p.299-319

Mayo, Deborah G.

2005

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Experimental Practice and an Error Statistical Account of Evidence

Philosophy of science, 2000-09, Vol.67 (3), p.S193-S207

Mayo, Deborah G.

2000

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Some Methodological Issues in Experimental Economics

Philosophy of science, 2008-12, Vol.75 (5), p.633-645

Mayo, Deborah

2008

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How Can We Cultivate Senn's Abilirty

Rationality, markets and morals, 2012, Vol.3 (51)

Mayo, Deborah

2012

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Statistical Science and Philosophy of Science: Whrer Do / Should They Meet in 2011 (and Beyond)?

Rationality, markets and morals, 2011, Vol.2 (44)

Mayo, Deborah

2011

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Novel work on problems of novelty? Comments on Hudson

Studies in History and Philosophy of Modern Physics, 2003-03, Vol.34 (1), p.131-134

Mayo, Deborah G.

2003

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The statistics wars and intellectual conflicts of interest

P‐value thresholds: Forfeit at your peril

Statistical significance and its critics: practicing damaging science, or damaging scientific practice?

Significance Tests: Vitiated or Vindicated by the Replication Crisis in Psychology?

On the Birnbaum Argument for the Strong Likelihood Principle

Severe Testing as a Basic Concept in a Neyman–Pearson Philosophy of Induction

Remembering Sir David Cox, 1924–2022

Error statistical modeling and inference: Where methodology meets ontology

Statistics, philosophy, and health: the SMAC 2021 webconference

Rejoinder: "On the Birnbaum Argument for the Strong Likelihood Principle"

The error-statistical philosophy and the practice of Bayesian statistics: Comments on Gelman and Shalizi: 'Philosophy and the practice of Bayesian statistics'

Ontology & methodology

Methodology in Practice: Statistical Misspecification Testing

How to Discount Double-Counting When It Counts: Some Clarifications

Five ways to ensure that models serve society: a manifesto

Philosophical Scrutiny of Evidence of Risks: From Bioethics to Bioevidence

In Regard to Fornacon-Wood et al

Discussion: Bayesian Methods: Applied? Yes. Philosophical Defense? In Flux

When Can Risk-Factor Epidemiology Provide Reliable Tests?

Peircean Induction and the Error-Correcting Thesis

Experimental Practice and an Error Statistical Account of Evidence

Some Methodological Issues in Experimental Economics

How Can We Cultivate Senn's Abilirty

Statistical Science and Philosophy of Science: Whrer Do / Should They Meet in 2011 (and Beyond)?

Novel work on problems of novelty? Comments on Hudson

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