Correlations in Social Neuroscience Aren't Voodoo: Commentary on Vul et al. (2009).

Correlations in Social Neuroscience Aren't Voodoo: Commentary on Vul et al. (2009).
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社会神经科学的相关性不是Voodoo:对Vul等人的评论。 (2009)。

DOI:
10.1111/j.1745-6924.2009.01128.x
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发表时间:
2009-05
期刊:
Perspectives on psychological science : a journal of the Association for Psychological Science
影响因子:
--
通讯作者:
Wager TD
Wager TD
中科院分区:
其他
文献类型:
--
作者:
Lieberman MD;Berkman ET;Wager TD

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,本期)声称功能磁共振成像研究中的许多大脑与人格相关性“可能……是虚假的”(第 274 页),并且“不应相信”(第 285 页)。他们的一些结论是不正确的。首先,他们错误地声称全脑回归使用了无效且“非独立”的两步推理程序,这一决定基于发送给研究人员的一项调查,该调查仅包括有关绘制数据的描述性过程的非诊断性问题。我们解释了全脑回归如何成为识别与个体差异测量具有可靠相关性的大脑区域的有效单步方法。其次,他们声称全脑回归分析的巨大相关性可能只是噪音的结果。我们提供了一个模拟来证明,在没有任何真实效果的情况下,典型的功能磁共振成像样本量很少会产生大的相关性。第三,他们声称所报告的相关性被夸大到“高得令人难以置信”。尽管有偏差的事后相关性估计是进行多次测试的众所周知的结果,但 Vul 等人。在估计此类相关性的理论上限时做出不准确的假设。此外,他们自己的“荟萃分析”表明偏差的大小约为 0.12——一个相当温和的偏差。
, this issue) claim that many brain–personality correlations in fMRI studies are “likely…spurious” (p. 274), and “should not be believed” (p. 285). Several of their conclusions are incorrect. First, they incorrectly claim that whole-brain regressions use an invalid and “nonindependent” two-step inferential procedure, a determination based on a survey sent to researchers that only included nondiagnostic questions about the descriptive process of plotting one’s data. We explain how whole-brain regressions are a valid single-step method of identifying brain regions that have reliable correlations with individual difference measures. Second, they claim that large correlations from whole-brain regression analyses may be the result of noise alone. We provide a simulation to demonstrate that typical fMRI sample sizes will only rarely produce large correlations in the absence of any true effect. Third, they claim that the reported correlations are inflated to the point of being “implausibly high.” Though biased post hoc correlation estimates are a well-known consequence of conducting multiple tests, Vul et al. make inaccurate assumptions when estimating the theoretical ceiling of such correlations. Moreover, their own “meta-analysis” suggests that the magnitude of the bias is approximately .12—a rather modest bias.
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