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FACTOR: A computer program to fit the exploratory factor analysis model

机译:因子:适合探索性因子分析模型的计算机程序

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Exploratory factor analysis (EFA) is one of the most widely used statistical procedures in psychological research. It is a classic technique, but statistical research into EFA is still quite active, and various new developments and methods have been presented in recent years. The authors of the most popular statistical packages, however, do not seem very interested in incorporating these new advances. We present the program FACTOR, which was designed as a general, user-friendly program for computing EFA. It implements traditional procedures and indices and incorporates the benefits of some more recent developments. Two of the traditional procedures implemented are polychoric correlations and parallel analysis, the latter of which is considered to be one of the best methods for determining the number of factors or components to be retained. Good examples of the most recent developments implemented in our program are (1) minimum rank factor analysis, which is the only factor method that allows one to compute the proportion of variance explained by each factor, and (2) the simplimax rotation method, which has proved to be the most powerful rotation method available. Of these methods, only polychoric correlations are available in some commercial programs. A copy of the software, a demo, and a short manual can be obtained free of charge from the first author.
机译:探索性因素分析(EFA)是心理学研究中使用最广泛的统计程序之一。这是一项经典技术,但是对全民教育的统计研究仍然非常活跃,并且近年来出现了各种新的发展和方法。但是,最受欢迎的统计软件包的作者似乎对合并这些新进展并不十分感兴趣。我们介绍了FACTOR程序,该程序被设计为用于计算EFA的通用,易于使用的程序。它执行传统的程序和索引,并结合了一些最新发展的好处。实施的两个传统程序是多色相关和并行分析,后者被认为是确定要保留的因子或成分数量的最佳方法之一。在我们的程序中实现的最新发展的很好的例子是:(1)最小秩因子分析,这是唯一一种可以计算每个因子解释的方差比例的因子方法;以及(2)simplimax旋转方法,已被证明是最强大的旋转方法。在这些方法中,某些商业程序中仅多色相关性可用。可以从第一作者免费获得软件的副本,演示和简短的手册。

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