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遗忘中的真实幂函数曲线:个体遗忘函数的定量分析

Genuine power curves in forgetting: a quantitative analysis of individual subject forgetting functions.

作者信息

Wixted J T, Ebbesen E B

机构信息

Department of Psychology, University of California San Diego, La Jolla 92093-0109, USA.

出版信息

Mem Cognit. 1997 Sep;25(5):731-9. doi: 10.3758/bf03211316.

Abstract

Wixted and Ebbesen (1991) showed that forgetting functions produced by a variety of procedures are often well described by the power function, at-b, where a and b are free parameters. However, all of their analyses were based on data arithmetically averaged over subjects. R. B. Anderson and Tweney (1997) argue that the power law of forgetting may be an artifact of arithmetically averaging individual subject forgetting functions that are truly exponential in form and that geometric averaging would avoid this potential problem. We agree that researchers should always be cognizant of the possibility of averaging artifacts, but we also show that our conclusions about the form of forgetting remain unchanged (and goodness-of-fit statistics are scarcely affected by) whether arithmetic or geometric averaging is used. In addition, an analysis of individual subject forgetting functions shows that they, too, are described much better by a power function than by an exponential.

摘要

威克斯泰德和埃贝森(1991)表明,由各种程序产生的遗忘函数通常能用幂函数(a\times t^{-b})很好地描述,其中(a)和(b)是自由参数。然而,他们所有的分析都是基于对受试者进行算术平均后的数据。R. B. 安德森和特威尼(1997)认为,遗忘的幂律可能是对个体受试者真正呈指数形式的遗忘函数进行算术平均的人为产物,而几何平均可以避免这个潜在问题。我们同意研究人员应该始终意识到平均人为产物的可能性,但我们也表明,无论使用算术平均还是几何平均,我们关于遗忘形式的结论都保持不变(并且拟合优度统计几乎不受影响)。此外,对个体受试者遗忘函数的分析表明,幂函数对它们的描述也比对指数函数的描述好得多。

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