Resum
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.
Idioma original | Anglès |
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Pàgines (de-a) | 534-547 |
Nombre de pàgines | 14 |
Revista | Journal of Experimental Psychology: General |
Volum | 143 |
Número | 2 |
DOIs | |
Estat de la publicació | Publicada - d’abr. 2014 |
Publicat externament | Sí |