Analysis of individual variations in the classical horizontal-vertical illusion

Analysis of individual variations in the classical horizontal-vertical illusion
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DOI:
10.3758/app.72.4.1045
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发表时间:
2010-05-01
影响因子:
1.7
通讯作者:
Hansen, Thorsten
Hansen, Thorsten
中科院分区:
心理学4区
文献类型:
--
作者:
Hamburger, Kai;Hansen, Thorsten

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在水平-垂直错觉(HVI)中,垂直线的长度被高估,而在平分错觉(BI)中,水平平分线被高估。在这里,我们的22名观察员中只有一半显示了预期的BI,而另一半则低估了平分线。观察者对HVI强度的判断也不同:表现出经典平分效应的观察者的HVI更强,而低估平分线的观察者的HVI更弱或不存在。为了解释这些结果,我们使用了一个线性模型来分别估计两个错觉背后的两个假定因素的强度。而强度的HVI和BI高度相关,估计的因素是不相关的。因此,在两个对照实验中,我们测量了纯水平垂直(pHVI)和平分(pBI)错觉。一个显着的相关性之间的估计因素和测量的错觉variables被发现。结果是强大的对比度,重复演示,并选择调整线的变化。因此,经典的HVI作为两个独立因素的加性组合得到了证实,但我们发现相当大的个体差异的强度的错觉。研究结果强调了分析个体数据的重要性,而不是采取样本手段来理解这些错觉。
In the horizontal-vertical illusion (HVI), the length of the vertical line is overestimated, whereas in the bisection illusion (BI), the horizontal bisecting line is expected to be overestimated. Here, only half of our 22 observers showed the expected BI, whereas the other half underestimated the bisecting line. Observers also differed in their judgments of the strength of the HVI: The HVI was stronger for observers showing the classical bisection effect, and weaker or absent for those underestimating the bisecting line. To account for these results, we used a linear model to individually estimate the strength of two putative factors underlying both illusions. Whereas the strength of the HVI and BI were highly correlated, the estimated factors were uncorrelated. Therefore, in two control experiments, we then measured the pure horizontal-vertical (pHVI) and bisection (pBI) illusions. A significant correlation between the estimated factors and the measured illusion variants was found. Results were robust against variations of contrast, repetitive presentations, and choice of adjusted line. Thus, the classical HVI as an additive combination of two independent factors was confirmed, but we found considerable interindividual variations in the strength of the illusions. The results stress the importance of analyzing individual data rather than taking sample means for understanding these illusions.