Exploratory Factor Analysis

D. Gunzler, A. Perzynski, A. Carle
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引用次数: 0

Abstract

It is important to distinguish between exploratory and confirmatory analysis. In an exploratory analysis, one wants to explore the empirical data to discover and detect characteristic features and interesting relationships without imposing any definite model on the data. An exploratory analysis may be structure generating, model generating, or hypothesis generating. In confirmatory analysis, on the other hand, one builds a model assumed to describe, explain, or account for the empirical data in terms of relatively few parameters. The model is based on a priori information about the data structure in the form of a specified theory or hypothesis, a given classificatory design for items or subtests according to objective features of content and format, known experimental conditions, or knowledge from previous studies based on extensive data.
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探索性因素分析
区分探索性分析和验证性分析是很重要的。在探索性分析中,人们希望通过探索经验数据来发现和检测特征和有趣的关系,而不给数据强加任何确定的模型。探索性分析可以是结构生成、模型生成或假设生成。另一方面,在验证性分析中,人们建立一个模型,假设用相对较少的参数来描述、解释或解释经验数据。该模型基于有关数据结构的先验信息,其形式为特定的理论或假设、根据内容和格式的客观特征对项目或子测试进行的给定分类设计、已知的实验条件或基于大量数据的先前研究的知识。
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