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贝叶斯分析多方法自我损耗研究支持零假设。

Bayesian analysis of multimethod ego-depletion studies favours the null hypothesis.

机构信息

Texas State University, San Marcos, TX, USA.

出版信息

Br J Soc Psychol. 2018 Apr;57(2):367-385. doi: 10.1111/bjso.12236. Epub 2018 Jan 4.

Abstract

Ego-depletion refers to the purported decrease in performance on a task requiring self-control after engaging in a previous task involving self-control, with self-control proposed to be a limited resource. Despite many published studies consistent with this hypothesis, recurrent null findings within our laboratory and indications of publication bias have called into question the validity of the depletion effect. This project used three depletion protocols involved three different depleting initial tasks followed by three different self-control tasks as dependent measures (total n = 840). For each method, effect sizes were not significantly different from zero When data were aggregated across the three different methods and examined meta-analytically, the pooled effect size was not significantly different from zero (for all priors evaluated, Hedges' g = 0.10 with 95% credibility interval of [-0.05, 0.24]) and Bayes factors reflected strong support for the null hypothesis (Bayes factor > 25 for all priors evaluated).

摘要

自我损耗是指在进行需要自我控制的先前任务后,执行后续任务时自我控制能力下降的现象,自我控制被认为是一种有限的资源。尽管有许多已发表的研究支持这一假设,但我们实验室的反复出现的无效结果和出版偏倚的迹象,使得自我损耗效应的有效性受到了质疑。本项目使用了三种损耗方案,涉及三个不同的初始损耗任务,随后是三个不同的自我控制任务作为因变量(总样本量为 840)。对于每种方法,效应大小均不显著不同于零。当数据在三种不同方法之间汇总并进行荟萃分析时,合并的效应大小也不显著不同于零(对于所有先验评估,Hedges' g = 0.10,95%可信度区间为[-0.05, 0.24]),贝叶斯因子反映了对零假设的强有力支持(对于所有先验评估,贝叶斯因子>25)。

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