在发现非不变性时发现不变性:使用因子比率测试和列表-删除过程的自动化执行部分度量不变性测试的说明性示例

IF 4 3区 管理学 Q1 INDUSTRIAL RELATIONS & LABOR
Bryn Hammack-Brown, Julia A. Fulmore, Greggory L. Keiffer, Kim Nimon
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引用次数: 2

摘要

在人力资源开发(HRD)研究中,群体之间的比较是常见的,然而许多研究者在分析和解释群体差异可能意味着什么之前忽略了一个至关重要的先决条件。从本质上讲,人力资源开发学者如何能够自信地知道,平均群体差异可归因于群体之间的实际差异,而不是每个群体如何解释兴趣结构的差异?测量不变性(Measurement invariance, MI)提供了对测量或构造在组间或随时间变化是否具有相同含义的洞察,是评估组间差异的重要先兆。虽然心肌梗死测试在HRD研究中获得了一些牵引力,但当需要部分心肌梗死测试时采取的步骤却很少受到关注。本文的目的是鼓励HRD研究人员和实践者在出现部分不变性(即非不变性)时采用并利用两种技术。在部分MI测试中可以使用几种技术;然而,本文所展示的因子比检验和列表删除程序是在验证性因子分析框架内建立的、可靠的和被证明的。本文提供了一个说明性示例,说明在发现非不变性时如何使用这些技术在项目级别识别不变性。此外,还包括R语法,允许这些技术的自动化。本文还讨论了发现非不变性并对部分MI进行检验的理论重要性和对研究者和实践者的启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Finding invariance when noninvariance is found: An illustrative example of conducting partial measurement invariance testing with the automation of the factor-ratio test and list-and-delete procedure

Comparisons between groups are common in human resource development (HRD) studies, yet many researchers neglect a crucial prerequisite step before analyzing and interpreting what group differences might mean. In essence, how can HRD scholars be confident in knowing that mean group differences are attributable to actual differences between groups as opposed to differences in how each group interprets the constructs of interest? Measurement invariance (MI) provides insight into whether a measure or construct has the same meaning between groups or over time and is an important precursor to the evaluation of group differences. While MI testing has gained some traction within HRD studies, steps to take when partial MI testing is needed have received very little attention. The purpose of this article is to encourage HRD researchers and practitioners to embrace and utilize two techniques when partial invariance (i.e., noninvariance) occurs. There are several techniques one could use during partial MI testing; however, the two showcased herein, the factor-ratio test and the list-and-delete procedure, are established, reliable, and proven within the confirmatory factor analysis framework. This article provides an illustrative example of how to use these techniques to identify invariance at the item level when noninvariance is found. Additionally, R syntax is included that allows for the automation of these techniques. The importance to theory and implications to researchers and practitioners of finding noninvariance and then testing for partial MI is also discussed.

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来源期刊
CiteScore
7.60
自引率
6.10%
发文量
19
期刊介绍: Human Resource Development Quarterly (HRDQ) is the first scholarly journal focused directly on the evolving field of human resource development (HRD). It provides a central focus for research on human resource development issues as well as the means for disseminating such research. HRDQ recognizes the interdisciplinary nature of the HRD field and brings together relevant research from the related fields, such as economics, education, management, sociology, and psychology. It provides an important link in the application of theory and research to HRD practice. HRDQ publishes scholarly work that addresses the theoretical foundations of HRD, HRD research, and evaluation of HRD interventions and contexts.
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