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克朗巴哈系数:经典的抗扰性。

Coefficient Alpha: The Resistance of a Classic.

机构信息

Universitat Autònoma de Barcelona.

出版信息

Psicothema. 2023 Feb;35(1):5-20. doi: 10.7334/psicothema2022.321.

Abstract

BACKGROUND

During the 20th century the alpha coefficient (α) was widely used in the estimation of the internal consistency reliability of test scores. After misuses were identified in the early 21st century alternatives became widespread, especially the omega coefficient (ω). Nowadays, α is re-emerging as an acceptable option for reliability estimation.

METHOD

A review of the recent academic contributions, journal publication habits and recommendations from normative texts was carried out to identify good practices in estimation of internal consistency reliability.

RESULTS

To guide the analysis, we propose a three-phase decision diagram, which includes item description, fit of the measurement model for the test, and choice of the reliability coefficient for test score(s). We also provide recommendations on the use of R, Jamovi, JASP, Mplus, SPSS and Stata software to perform the analysis.

CONCLUSIONS

Both α and ω are suitable for items with approximately normal distributions and approximately unidimensional and congeneric measures without extreme factor loadings. When items show non-normal distributions, strong specific components, or correlated errors, variants of ω are more appropriate. Some require specific data gathering designs. On a practical level we recommend a critical approach when using the software.

摘要

背景

在 20 世纪,α 系数(α)被广泛用于测试分数内部一致性可靠性的估计。21 世纪初,当发现了其误用后,替代方法变得广泛起来,尤其是 ω 系数(ω)。如今,α 再次成为可靠性估计的可接受选择。

方法

对最近的学术贡献、期刊出版习惯和规范文本的建议进行了回顾,以确定内部一致性可靠性估计的良好实践。

结果

为了指导分析,我们提出了一个三阶段决策图,包括项目描述、测试测量模型的拟合以及测试分数可靠性系数的选择。我们还就使用 R、Jamovi、JASP、Mplus、SPSS 和 Stata 软件进行分析提供了建议。

结论

α 和 ω 都适用于近似正态分布、近似单维和同类型的项目,且没有极端因子负荷。当项目显示非正态分布、强特定成分或相关误差时,ω 的变体更为合适。有些则需要特定的数据收集设计。在实际层面上,我们建议在使用软件时采取批判性的方法。

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