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J Exp Psychol Gen. 2014 Apr;143(2):534-47. doi: 10.1037/a0033242. Epub 2013 Jul 15.

P-curve: a key to the file-drawer.

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The Wharton School, University of Pennsylvania.
Haas School of Business, University of California.


Because scientists tend to report only studies (publication bias) or analyses (p-hacking) that "work," readers must ask, "Are these effects true, or do they merely reflect selective reporting?" We introduce p-curve as a way to answer this question. P-curve is the distribution of statistically significant p values for a set of studies (ps < .05). Because only true effects are expected to generate right-skewed p-curves-containing more low (.01s) than high (.04s) significant p values--only right-skewed p--curves are diagnostic of evidential value. By telling us whether we can rule out selective reporting as the sole explanation for a set of findings, p-curve offers a solution to the age-old inferential problems caused by file-drawers of failed studies and analyses.

[Indexed for MEDLINE]

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