statcheckis a free, open source R package that can be used to automatically extract statistical null-hypothesis significant testing (NHST) results from articles and recompute the p-values based on the reported test statistic and degrees of freedom to detect possible inconsistencies.
statcheckis mainly useful for:
statcheckto make sure your manuscript doesn’t contain copy-paste errors or other inconsistencies before you submit it to a journal.
statcheckto check submitted manuscripts for statistical inconsistencies. They can ask authors for a correction or clarification before publishing a manuscript.
statcheckcan 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), or use it to analyze p-value distributions (see e.g., Hartgerink et al., 2016).
The algorithm behind
statcheckconsists of four basic steps:
statcheckcan 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.
Errorin 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 (
DecisionErrorin the output).
statchecktakes 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.
statcheck.io is a web-based interface for statcheck.