Since factor analysis is one of the most often used techniques in psychometrics, comparing or combining solutions from different factor analyses is often needed. Several measures to compare factors exist, one of the best known is Tucker’s congruence coefficient, which is enjoying newly found popularity thanks to the recent work of Lorenzo-Seva and ten Berge (2006), who established cut-off values for factor congruence. While this coefficient is in most cases very good in comparing factors in general, it also has some disadvantages, which can cause trouble when one needs to compare or combine many analyses. In this paper, we propose a modified Tucker’s congruence coefficient to address these issues.

中文翻译：

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用于因子匹配的改进的塔克全等系数

由于因子分析是心理计量学中最常用的技术之一，因此经常需要比较或组合来自不同因子分析的解决方案。存在几种比较因素的措施，其中最著名的一种是塔克的同余系数，这得益于Lorenzo-Seva和10 Berge（2006）的最新工作，他们确定了因素同余的临界值。尽管该系数通常在大多数情况下可以很好地比较因素，但它也有一些缺点，当需要比较或组合许多分析时，可能会造成麻烦。在本文中，我们提出了一个修正的塔克全等系数来解决这些问题。