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从个体分布构建群体分布。

Constructing a group distribution from individual distributions.

作者信息

Cousineau Denis, Thivierge Jean-Philippe, Harding Bradley, Lacouture Yves

机构信息

École de psychologie.

École de psychologie, Université Laval.

出版信息

Can J Exp Psychol. 2016 Sep;70(3):253-277. doi: 10.1037/cep0000069. Epub 2015 Nov 16.

Abstract

A group distribution is a synthesis of a set of individual distributions. To be adequate, a method for creating group distributions should not introduce characteristics that are not present in the individual distributions and preserve those that are present. A method occasionally used is quantile averaging (sometimes called vincentizations), applied generally to response time distributions. However, it is shown here using quantile-quantile plots on empirical response times that this method is inadequate. As shown by Thomas and Ross (1980, Journal of Mathematical Psychology), to solve this problem, quantile averaging can be generalised using an appropriate nonlinear transformation of the data. Here we argue that the correct transformation is the log transform of response times to which the base response time has been removed. Equivalently, the geometric mean of the quantiles can be used. We first propose 4 estimates of the base response times. We next examine empirical data in a same-different task, in a redundant-attribute target detection task and in a visual search task. The results show that this approach is appropriate to construct group distributions. It can be used to aggregate distributions over multiple participants, over multiple sessions of training for a given participant, or both. (PsycINFO Database Record

摘要

组分布是一组个体分布的综合。要做到恰当,创建组分布的方法不应引入个体分布中不存在的特征,而应保留那些存在的特征。一种偶尔使用的方法是分位数平均(有时称为文森特化),通常应用于反应时间分布。然而,本文通过对经验反应时间使用分位数 - 分位数图表明,这种方法是不恰当的。正如托马斯和罗斯(1980年,《数学心理学杂志》)所表明的,为了解决这个问题,可以使用数据的适当非线性变换来推广分位数平均。在这里,我们认为正确的变换是去除了基本反应时间的反应时间的对数变换。等效地,可以使用分位数的几何平均数。我们首先提出4种基本反应时间的估计方法。接下来,我们在异同任务、冗余属性目标检测任务和视觉搜索任务中检验经验数据。结果表明,这种方法适用于构建组分布。它可用于汇总多个参与者的分布、给定参与者多次训练阶段的分布,或两者兼而有之。(PsycINFO数据库记录)

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