About this resource

    Type of resources
    Primary Source, Reading, Paper
    Education level(s)
    College / Upper Division (Undergraduates)
    Primary user(s)
    Student
    Subject area(s)
    Math & Statistics, Social Science
    Language(s)
    English
    Cluster
    Replication and Meta-Research, Conceptual and Statistical Knowledge
    Last updated
    29 October 2026
    Primary SourceReadingPaper

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

    By Uri Simonsohn, Leif D. Nelson, Joseph P. Simmons

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    Level College / Upper Division (Undergraduates) · For Student · Language English

    Abstract

    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.

    Keywords Reproducibility Crisis and Credibility Revolution