Inflated effect sizes and underpowered tests: how the severity measure of evidence is affected by the winner’s curse
Author:
Publisher
Springer Science and Business Media LLC
Subject
Philosophy
Link
http://link.springer.com/content/pdf/10.1007/s11098-020-01424-z.pdf
Reference8 articles.
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2. Gelman, A., & Carlin, J. (2014). Beyond power calculations assessing type s (sign) and type m (magnitude) errors. Perspectives on Psychological Science, 9(6), 641–651.
3. Ioannidis, J. P. (2008). Why most discovered true associations are inflated. Epidemiology, 19(5), 640–648.
4. Ioannidis, J. P. A., Stanley, T. D., & Doucouliagos, H. (2017). The power of bias in economics research. The Economic Journal, 127(605), F236–F265.
5. Mayo, D. G., & Spanos, A. (2006). Severe testing as a basic concept in a Neyman–Pearson philosophy of induction. The British Journal for the Philosophy of Science, 57(2), 323–357.
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