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Confidence Intervals Make a Difference: Effects of Showing Confidence Intervals on Inferential Reasoning

机译:置信区间会有所作为:显示置信区间对推理推理的影响

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The use of confidence intervals (CIs) as an addition or as an alternative to null hypothesis significance testing (NHST) has been promoted as a means to make researchers more aware of the uncertainty that is inherent in statistical inference. Little is known, however, about whether presenting results via CIs affects how readers judge the probability that an effect is present in the population of interest and whether a replication would be likely to reveal the same results. In the present study, 66 PhD students were asked to interpret statistical outcomes presented as CIs or as conventional statistics (t statistics and associated p values). Fewer misinterpretations of statistics-such as accepting the null hypothesis-and more references to effect size were found when results were presented as CIs. Furthermore, participants tended to be more certain about the existence of a population effect in the expected direction and about the replicability of the results when the results were presented following the conventions of NHST than when presented using CIs. Contrary to expectations, no evidence of a more precipitous drop in the belief of the existence of a population effect and replicability estimates when p values exceeded the significance level of. 05 was found when data were presented using NHST instead of by CIs.
机译:提倡使用置信区间(CIs)作为零假设重要性检验(NHST)的补充或替代方法,以使研究人员更加了解统计推断固有的不确定性。但是,关于通过CI呈现结果是否会影响读者如何判断感兴趣的人群中是否存在效果以及复制是否可能揭示相同结果的知之甚少。在本研究中,要求66名博士生解释以CI或常规统计(t统计和相关的p值)表示的统计结果。当结果以CI表示时,发现对统计数据的误解更少(例如接受原假设),并且发现了更多的影响大小参考。此外,与使用CIs相比,按照NHST惯例提交结果时,与会人员更倾向于确定人口效应在预期方向上的存在以及结果的可复制性。与预期相反,当p值超过的显着性水平时,没有证据表明存在种群效应和可复制性估计的信念更加急剧地下降。使用NHST而不是CI表示数据时发现05。

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