Erroneous generalization-Exploring random error variance in reliability generalizations of psychological measurements.

IF 7.6 1区 心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
Lukas J Beinhauer, Jens H Fünderich, Frank Renkewitz
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引用次数: 0

Abstract

Reliability generalization (RG) studies frequently interpret meta-analytic heterogeneity in score reliability as evidence of differences in an instrument's measurement quality across administrations. However, such interpretations ignore the fact that, under classical test theory, score reliability depends on two parameters: true score variance and error score variance. True score variance refers to the actual variation in the trait we aim to measure, while error score variance refers to nonsystematic variation arising in the observed, manifest variable. If the error score variance remains constant, variations in true score variance can result in heterogeneity in reliability coefficients. While this argument is not new, we argue that current approaches to addressing this issue in the RG literature are insufficient. Instead, we propose enriching an RG study with Boot-Err: Explicitly modeling the error score variance using bootstrapping and meta-analytic techniques. Through a comprehensive simulation scheme, we demonstrate that score reliability can vary while the measuring quality remains unaffected. The simulation also illustrates how explicitly modeling error score variances may improve inferences concerning random measurement error and under which conditions such enhancements occur. Furthermore, using openly available direct replication data, we show how explicitly modeling error score variance allows for an assessment to what extent measurement quality can be described as identical across administration sites. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

错误概化——探讨心理测量信度概化中的随机误差方差。
可靠性泛化(RG)研究经常解释得分可靠性的元分析异质性,作为不同行政部门间测量质量差异的证据。然而,这种解释忽略了一个事实,即在经典测试理论下,分数信度取决于两个参数:真分数方差和错误分数方差。真实得分方差是指我们要测量的性状的实际变异,而误差得分方差是指观察到的表现变量产生的非系统变异。如果误差分数方差保持不变,真实分数方差的变化会导致信度系数的异质性。虽然这一观点并不新鲜,但我们认为目前在RG文献中解决这一问题的方法是不够的。相反,我们建议使用Boot-Err来丰富RG研究:使用引导和元分析技术显式地建模错误得分方差。通过一个综合的模拟方案,我们证明分数的可靠性可以改变,而测量质量不受影响。仿真还说明了如何显式地建模误差分数方差可以改善有关随机测量误差的推断,以及在哪些条件下会发生这种增强。此外,使用公开可用的直接复制数据,我们展示了如何显式建模误差评分方差允许评估在多大程度上度量质量可以被描述为跨管理站点相同。(PsycInfo Database Record (c) 2025 APA,版权所有)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Psychological methods
Psychological methods PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
13.10
自引率
7.10%
发文量
159
期刊介绍: Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.
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