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如果删除项目时的α系数:关于在量表编制中为使α系数最大化而导致效标效度丧失的一则说明。

Alpha if item deleted: a note on loss of criterion validity in scale development if maximizing coefficient alpha.

作者信息

Raykov Tenko

机构信息

Measurement and Quantitative Methods, Michigan State University, East Lansing, MI 48824, USA.

出版信息

Br J Math Stat Psychol. 2008 Nov;61(Pt 2):275-85. doi: 10.1348/000711007X188520. Epub 2007 Apr 12.

Abstract

This note is concerned with a validity-related limitation of the widely available and routinely used index 'alpha if item deleted' in the process of construction and development of multiple-component measuring instruments. Attention is drawn to the fact that this statistic can suggest dispensing with such scale components, whose removal leads to loss of criterion validity while maximizing the popular coefficient alpha. As an alternative, a latent variable modelling approach is discussed that can be used for point and interval estimation of composite criterion validity (as well as reliability) after deletion of single components. The method can also be utilized to test conventional or minimum level hypotheses about associated population change in measurement quality indices.

摘要

本笔记关注的是在多成分测量工具的构建和开发过程中,广泛使用且常规应用的“删除项目后的α系数”指标与效度相关的局限性。需注意的是,该统计量可能会建议舍弃某些量表成分,而去除这些成分虽能使广为人知的α系数最大化,但却会导致效标效度的损失。作为一种替代方法,本文讨论了一种潜在变量建模方法,该方法可用于在删除单个成分后对复合效标效度(以及信度)进行点估计和区间估计。该方法还可用于检验关于测量质量指标相关总体变化的传统假设或最低水平假设。

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