“statcheck”: Automatically detect statistical reporting inconsistencies to increase reproducibility of meta-analyses.

Michèle Nuijten*, Joshua Polanin

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Downloads (Pure)

Abstract

We present the R package and web app statcheck to automatically detect statistical reporting inconsistencies in primary studies and meta‐analyses. Previous research has shown a high prevalence of reported p‐values that are inconsistent ‐ meaning a re‐calculated p‐value, based on the reported test statistic and degrees of freedom, does not match the author‐reported p‐value. Such inconsistencies affect the reproducibility and evidential value of published findings. The tool statcheck can help researchers to identify statistical inconsistencies so that they may correct them. In this paper, we provide an overview of the prevalence and consequences of statistical reporting inconsistencies. We also discuss the tool statcheck in more detail and give an example of how it can be used in a meta‐analysis. We end with some recommendations concerning the use of statcheck in meta‐analyses and make a case for better reporting standards of statistical results.
Original languageEnglish
Number of pages6
JournalResearch Synthesis Methods
DOIs
Publication statusE-pub ahead of print - 2020

Keywords

  • PSYCHOLOGY
  • PUBLICATION DECISIONS
  • TESTS
  • meta-analysis
  • reporting standards
  • reproducibility
  • statcheck
  • statistical error

Fingerprint Dive into the research topics of '“statcheck”: Automatically detect statistical reporting inconsistencies to increase reproducibility of meta-analyses.'. Together they form a unique fingerprint.

  • Cite this