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

机译:通过算法识别公布的比率与其报告的置信区间和P值之间的差异

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摘要

MotivationStudies, 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.
机译:动机研究(主要来自操作/管理文献)表明,人为错误的发生率会随着任务的复杂性而增加。由于必须经过同行评审,所以不知道是多少错误使该错误成为了已出版的文献。通过在文本中标识成对的相关值以进行复杂程度不同的报告计算,我们可以标识差异,量化错误率并标识缓解因素。

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