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Abstract：
Combining data from different studies has a long tradition within the scientific community. It requires that the same information is collected from each study to be able to pool individual data. When studies have implemented different methods or used different instruments (e.g., questionnaires) for measuring the same characteristics or constructs, the observed variables need to be harmonized in some way to obtain equivalent content information across studies. This paper formulates the main concepts for harmonizing test scores from different observational studies in terms of latent variable models. The concepts are formulated in terms of calibration, invariance, and exchangeability. Although similar ideas are present in measurement reliability and test equating, harmonization is different from measurement invariance and generalizes test equating. In addition, if a test score needs to be transformed to another test score, harmonization of variables is only possible under specific conditions. Observed test scores that connect all of the different studies, are necessary to be able to test the underlying assumptions of harmonization. The concepts of harmonization are illustrated on multiple memory test scores from three different Canadian studies.
摘要：
将来自不同研究的数据结合起来在科学界有着悠久的传统。它要求从每个研究中收集相同的信息，以便能够汇集单个数据。当研究实施了不同的方法或使用了不同的仪器(例如，问卷)用于测量相同的特征或结构，观察到的变量需要以某种方式进行协调，以获得跨研究的等效内容信息。本文根据潜在变量模型，提出了协调不同观察性研究中的考试成绩的主要概念。这些概念是根据校准来制定的，不变性,和可交换性。尽管在测量可靠性和测试等同方面存在类似的想法，协调不同于测量不变性，概括了测试等同。此外,如果一个考试成绩需要转换为另一个考试成绩，变量的协调只有在特定条件下才有可能。观察到的测试分数连接了所有不同的研究，是必要的，以便能够测试协调的基本假设。在来自三个不同加拿大研究的多个记忆测试分数上说明了协调的概念。
