Algorithmic identification of discrepancies between published ratios and their reported confidence intervals and P-values.

ABSTRACT: Motivation:Studies, mostly from the operations/management literature, have shown that the rate of human error increases with task complexity. What is not known is how many errors make it into the published literature, given that they must slip by peer-review. By identifying paired, dependent values within text for reported calculations of varying complexity, we can identify discrepancies, quantify error rates and identify mitigating factors. Results:We extracted statistical ratios from MEDLINE abstracts (hazard ratio, odds ratio, relative risk), their 95% CIs, and their P-values. We re-calculated the ratios and P-values using the reported CIs. For comparison, we also extracted percent-ratio pairs, one of the simplest calculation tasks. Over 486 000 published values were found and analyzed

SUBMITTER: Georgescu C 

PROVIDER: S-EPMC5946902 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature