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Multiple Studies and Evidential Defeat

Noûs 47 (1):154-180 (2011)

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  1. Confirmation in a Branching World: The Everett Interpretation and Sleeping Beauty.Darren Bradley - 2011 - British Journal for the Philosophy of Science 62 (2):323-342.
    Sometimes we learn what the world is like, and sometimes we learn where in the world we are. Are there any interesting differences between the two kinds of cases? The main aim of this article is to argue that learning where we are in the world brings into view the same kind of observation selection effects that operate when sampling from a population. I will first explain what observation selection effects are ( Section 1 ) and how they are relevant (...)
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  • Four Problems about Self-Locating Belief.Darren Bradley - 2012 - Philosophical Review 121 (2):149-177.
    This article defends the Doomsday Argument, the Halfer Position in Sleeping Beauty, the Fine-Tuning Argument, and the applicability of Bayesian confirmation theory to the Everett interpretation of quantum mechanics. It will argue that all four problems have the same structure, and it gives a unified treatment that uses simple models of the cases and no controversial assumptions about confirmation or self-locating evidence. The article will argue that the troublesome feature of all these cases is not self-location but selection effects.
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  • Type I error rates are not usually inflated.Mark Rubin - manuscript
    The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Questionable research practices such as p-hacking are thought to inflate Type I error rates above their nominal level, leading to unexpectedly high levels of false positives in the literature and, consequently, unexpectedly low replication rates. In this article, I offer an alternative view. I argue that questionable and other research practices do not usually inflate relevant Type I error rates. I begin (...)
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  • When to adjust alpha during multiple testing: a consideration of disjunction, conjunction, and individual testing.Mark Rubin - 2021 - Synthese 199 (3-4):10969-11000.
    Scientists often adjust their significance threshold during null hypothesis significance testing in order to take into account multiple testing and multiple comparisons. This alpha adjustment has become particularly relevant in the context of the replication crisis in science. The present article considers the conditions in which this alpha adjustment is appropriate and the conditions in which it is inappropriate. A distinction is drawn between three types of multiple testing: disjunction testing, conjunction testing, and individual testing. It is argued that alpha (...)
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  • Multiple studies and weak evidential defeat.Nikk Effingham & Malcolm J. Price - 2017 - Theoretical Medicine and Bioethics 38 (5):353-366.
    When a study shows statistically significant correlation between an exposure and an outcome, the credence of a real connection between the two increases. Should that credence remain the same when it is discovered that further independent studies between the exposure and other independent outcomes were conducted? Matthew Kotzen argues that it should remain the same, even if the results of those further studies are discovered. However, we argue that it can differ dependent upon the results of the studies.
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  • Is phenomenal force sufficient for immediate perceptual justification?Lu Teng - 2018 - Synthese 195 (2):637-656.
    As an important view in the epistemology of perception, dogmatism proposes that for any experience, if it has a distinctive kind of phenomenal character, then it thereby provides us with immediate justification for beliefs about the external world. This paper rejects dogmatism by looking into the epistemology of imagining. In particular, this paper first appeals to some empirical studies on perceptual experiences and imaginings to show that it is possible for imaginings to have the distinctive phenomenal character dogmatists have in (...)
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  • Significance Testing in Theory and Practice.Daniel Greco - 2011 - British Journal for the Philosophy of Science 62 (3):607-637.
    Frequentism and Bayesianism represent very different approaches to hypothesis testing, and this presents a skeptical challenge for Bayesians. Given that most empirical research uses frequentist methods, why (if at all) should we rely on it? While it is well known that there are conditions under which Bayesian and frequentist methods agree, without some reason to think these conditions are typically met, the Bayesian hasn’t shown why we are usually safe in relying on results reported by significance testers. In this article, (...)
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  • Statistical Inference as Severe Testing: How to Get beyond the Statistics.Conor Mayo-Wilson - 2021 - Philosophical Review 130 (1):185-189.
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