Factor analysis of ordinal variables:: A comparison of three approaches
Factor analysis of ordinal variables:: A comparison of three approaches
复制标题
DOI：
10.1207/s15327906347-387
复制
发表时间：
2001-01-01
影响因子：
3.8
通讯作者：
Moustaki, I
中科院分区：
文献类型：
--
作者：
Jöreskog, KG;Moustaki, I
对于连续变量，探索性因子分析的理论和方法已经得到了很好的发展。在实践中，观察到的或测量到的变量通常是有序的。然而，序数通常被忽略，而像1、2、3、4这样表示有序类别的数字被视为具有度量属性的数字，这一过程在很多方面都是不正确的。在本文中，我们描述了四种适当考虑序数变量的因子分析方法，并比较了其中三种方法的参数估计和拟合。比较了两者在方法上的相对优势，并以一个经验数据示例和两个生成数据示例进行了比较。我们特别讨论了如何检验模型和测量模型拟合的问题。
Theory and methodology for exploratory factor analysis have been well developed for continuous variables. In practice, observed or measured variables are often ordinal. However, ordinality is most often ignored and numbers such as 1, 2, 3, 4, representing ordered categories, are treated as numbers having metric properties, a procedure which is incorrect in several ways. In this article we describe four approaches to factor analysis of ordinal variables which take proper account of ordinality and compare three of them with respect to parameter estimates and fit. The comparison is made both in terms of their relative methodological advantages and in terms of an empirical data example and two generated data examples. In particular, we discuss the issue of how to test the model and to measure model fit.