University of Leipzig, Germany; University of Frankfurt, Germany.
University of Cologne, Germany; University of Münster, Germany.
Soc Sci Res. 2023 Feb;110:102805. doi: 10.1016/j.ssresearch.2022.102805. Epub 2022 Oct 31.
This review summarizes the current state of the art of statistical and (survey) methodological research on measurement (non)invariance, which is considered a core challenge for the comparative social sciences. After outlining the historical roots, conceptual details, and standard procedures for measurement invariance testing, the paper focuses in particular on the statistical developments that have been achieved in the last 10 years. These include Bayesian approximate measurement invariance, the alignment method, measurement invariance testing within the multilevel modeling framework, mixture multigroup factor analysis, the measurement invariance explorer, and the response shift-true change decomposition approach. Furthermore, the contribution of survey methodological research to the construction of invariant measurement instruments is explicitly addressed and highlighted, including the issues of design decisions, pretesting, scale adoption, and translation. The paper ends with an outlook on future research perspectives.
本文综述了当前统计和（调查）方法学研究在测量（非）不变性方面的最新进展，这被认为是比较社会科学的核心挑战。在概述测量不变性检验的历史根源、概念细节和标准程序之后，本文特别关注了过去 10 年中取得的统计进展。这些进展包括贝叶斯近似测量不变性、对齐方法、多层次建模框架内的测量不变性检验、混合多群组因子分析、测量不变性探索器以及响应转移-真实变化分解方法。此外，还明确提出并强调了调查方法学研究在构建不变测量工具方面的贡献，包括设计决策、预测试、量表采用和翻译等问题。本文最后展望了未来的研究方向。
