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:
- Self-checks: you can use
statcheck
to make sure your manuscript doesn’t contain copy-paste errors or other inconsistencies before you submit it to a journal. - Peer review: editors and reviewers can use
statcheck
to check submitted manuscripts for statistical inconsistencies. They can ask authors for a correction or clarification before publishing a manuscript. - Research:
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:
- Convert pdf and html articles to plain text files.
-
Search the text for instances of NHST results. Specifically,
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. - Recompute the p-value using the reported test statistic and degrees of freedom.
-
Compare the reported and recomputed p-value. If the reported
p-value does not match the computed one, the result is marked as
an inconsistency (
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.