The likelihood principle and the reliability of experiments
Philosophy of Science 66 (3):361 (1999)
| Abstract | The likelihood principle of Bayesian statistics implies that information about the stopping rule used to collect evidence does not enter into the statistical analysis. This consequence confers an apparent advantage on Bayesian statistics over frequentist statistics. In the present paper, I argue that information about the stopping rule is nevertheless of value for an assessment of the reliability of the experiment, which is a pre-experimental measure of how well a contemplated procedure is expected to discriminate between hypotheses. I show that, when reliability assessments enter into inquiries, some stopping rules prescribing optional stopping are unacceptable to both Bayesians and frequentists | |||||||||
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Barry Loewer, Robert Laddaga & Roger Rosenkrantz (1978). On The Likelihood Principle and a Supposed Antinomy. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1978:279 - 286.
Peter Murphy (2006). Reliability Connections Between Conceivability and Inconceivability. Dialectica 60 (2):195-205.
Jan Sprenger (2009). Evidence and Experimental Design in Sequential Trials. Philosophy of Science 76 (5).
Erik J. Olsson & Stefan Schubert (2007). Reliability Conducive Measures of Coherence. Synthese 157 (3):297 - 308.
Robert Audi (2009). Reliability as a Virtue. Philosophical Studies 142 (1):43 - 54.
Anton Vedder & Robert Wachbroit (2003). Reliability of Information on the Internet: Some Distinctions. Ethics and Information Technology 5 (4):211-215.
Daniel Steel (2007). Bayesian Confirmation Theory and the Likelihood Principle. Synthese 156 (1):53 - 77.
Daniel Steel (2003). A Bayesian Way to Make Stopping Rules Matter. Erkenntnis 58 (2):213--227.
Andreas Jarvstad & Ulrike Hahn (2011). Source Reliability and the Conjunction Fallacy. Cognitive Science 35 (4):682-711.
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