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自我提升研究中的抑制效应:对基于条件的回归分析的批判性评论。

Suppressor effects in self-enhancement research: A critical comment on condition-based regression analysis.

机构信息

Department of Psychology, Heidelberg University.

出版信息

J Pers Soc Psychol. 2021 Oct;121(4):792-795. doi: 10.1037/pspa0000273. Epub 2021 Sep 13.

Abstract

Self-enhancement conceived as a positive relation between happiness (H) and the difference S-O (self-rating S minus objective measure O) is inherently confounded with a positive self-view account: S alone may explain the positive relation to H. Condition-based regression analysis (CRA; Humberg et al., 2018a, 2018b) promises a solution. CRA assumes that opposite predictor weights (βS > 0; βO < 0) in regression of H on S and O rule out that H depends on S alone. However, despite the truism that two significant regression weights imply that both S and O contribute to the prediction model, they cannot rule out a positive self-view account. If only S shares variance with H, O may improve the prediction indirectly, by suppressing unpredictive S-variance in the prediction model. Granting S-O-redundancy, a classical suppressor effect (Conger & Jackson, 1972) results in a negative regression weight for O (binding S-variance that is unpredictive of H). Thus, the regression pattern that CRA presumes to rule out a positive self-view account indeed follows necessarily from a suppressor effect entailed in a positive self-view account. Computer simulations illustrate and corroborate this critique. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

摘要

自我增强被理解为幸福感 (H) 与自我评分 (S) 与客观测量 (O) 之差 (S-O) 之间的积极关系,它与积极的自我观解释固有地混淆在一起:仅 S 可能解释与 H 的正相关关系。基于条件的回归分析 (CRA; Humberg 等人,2018a,2018b) 提供了一种解决方案。CRA 假设,在 S 和 O 对 H 的回归中,相反的预测权重 (βS > 0; βO < 0) 排除了 H 仅取决于 S 的情况。然而,尽管有这样一个事实,即两个显著的回归权重意味着 S 和 O 都对预测模型有贡献,但它们不能排除积极的自我观解释。如果只有 S 与 H 共享方差,那么 O 可能会通过抑制预测模型中不可预测的 S 方差间接提高预测,这就是经典的抑制效应 (Conger & Jackson, 1972)。因此,CRA 假定可以排除积极的自我观解释的回归模式确实必然来自积极的自我观解释所包含的抑制效应。计算机模拟说明了这一批评并进行了证实。(PsycInfo 数据库记录(c)2021 APA,保留所有权利)。

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