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statcheck
is a “spellchecker” for statistics. It checks whether your p-values match their accompanying test statistic and degrees of freedom.
statcheck
searches for null-hypothesis significance test (NHST) in APA style (e.g., t(28) = 2.2, p < .05). It recalculates the p-value using the reported test statistic and degrees of freedom. If the reported and computed p-values don’t match, statcheck
will flag the result as an error.
statcheck
is mainly useful for:
statcheck
to make sure your manuscript doesn’t contain copy-paste errors or other inconsistencies before you submit it to a journal.statcheck
to check submitted manuscripts for statistical inconsistencies. They can ask authors for a correction or clarification before publishing a manuscript.statcheck
can be used to automatically extract statistical test results from articles that can then be analyzed. You can for instance investigate whether you can predict statistical inconsistencies (see e.g., Nuijten et al., 2017 doi:10.1525/collabra.102), or use it to analyze p-value distributions (see e.g., Hartgerink et al., 2016 doi:10.7717/peerj.1935).The algorithm behind statcheck
consists of four basic steps:
statcheck
can recognize t-tests, F-tests, correlations, z-tests, \(\chi^2\) -tests, and Q-tests (from meta-analyses) if they are reported completely (test statistic, degrees of freedom, and p-value) and in APA style.error
in the output). If the reported p-value is significant and the computed is not, or vice versa, the result is marked as a gross inconsistency (decision_error
in the output).statcheck
takes into account correct rounding of the test statistic, and has the option to take into account one-tailed testing. See the manual for details.
For detailed information about installing and using statcheck
, see the manual on RPubs.
Also see statcheck.io, a web-based interface for statcheck.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.