Child and Family Studies, Leiden University, The Netherlands.
J Pers Assess. 2012;94(1):12-25. doi: 10.1080/00223891.2011.627965.
This article is set up as a tutorial for nonlinear principal components analysis (NLPCA), systematically guiding the reader through the process of analyzing actual data on personality assessment by the Rorschach Inkblot Test. NLPCA is a more flexible alternative to linear PCA that can handle the analysis of possibly nonlinearly related variables with different types of measurement level. The method is particularly suited to analyze nominal (qualitative) and ordinal (e.g., Likert-type) data, possibly combined with numeric data. The program CATPCA from the Categories module in SPSS is used in the analyses, but the method description can easily be generalized to other software packages.
本文旨在为非线性主成分分析（NLPCA）提供教程，系统地引导读者通过罗夏墨迹测验进行人格评估的实际数据分析。NLPCA 是线性 PCA 的一种更灵活的替代方法，它可以处理具有不同测量水平的非线性相关变量的分析。该方法特别适用于分析名义（定性）和有序（例如，Likert 型）数据，可能与数值数据相结合。分析中使用了 SPSS 中的 Categories 模块中的 CATPCA 程序，但方法描述可以轻松推广到其他软件包。
