相关性对个人意味着什么:研究人员、学生和公众的教程

R. Mõttus
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摘要

三分和交叉表(TACT)两个相关变量显示了它们的相关性对个体的意义。例如,了解一个人的责任心(在其他人中最低、中等或最高的三分之一)可以使预测其健康状况的准确性提高1.4个百分点,预测其子女的责任心的准确性提高4.2个百分点,预测其工作表现的准确性提高7.2个百分点,而随机猜测的准确性为33.3%。有35%的可能性在几年后他们的得分会有所不同,有50%的可能性他们的伴侣会对他们的责任心有不同的评价。对于心理学中的典型相关性,在一个变量中具有低值或高值的个体中,约有40%在另一个变量中具有相似的值,而中等值几乎没有预测信息。因此,相关性的直觉解释,如“x高的人可能y高”,几乎总是不正确的。为计算和可视化TACT提供了一个R包。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
What correlations mean for individual people: A tutorial for researchers, students and the public
Trisecting and cross-tabulating (TACT) two related variables shows what their correlation means for individual people. For example, knowing an individual's conscientiousness (lowest, medium or highest third among other people) improves the accuracy of predicting their health by 1.4, their child's conscientiousness by 4.2, and their job performance by 7.2 percentage points, compared to the random-guess accuracy of 33.3%. There’s a 35% probability that they will score differently in a few years and a 50% probability that their partner would rate their conscientiousness differently. For typical correlations in psychology, about 40% of individuals with a low or high value in one variable have a similar value in the other variable, while medium values carry almost no predictive information. Hence, correlations’ intuitive interpretations like "someone high in x is likely to be high in y" are almost always incorrect. An R package is provided for calculating and visualising TACT.
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