ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

心理科学进展 ›› 2010, Vol. 18 ›› Issue (12): 1991-1998.

• • 上一篇    

潜在类别分析技术在心理学研究中的应用

张洁婷;焦璨;张敏强   

  1. (1华南师范大学心理应用研究中心, 广州 510631) (2深圳大学师范学院心理学系, 深圳 518000)
  • 收稿日期:2010-05-04 修回日期:1900-01-01 出版日期:2010-12-15 发布日期:2010-12-15
  • 通讯作者: 张敏强

Application of Latent Class Analysis in Psychological Research

ZHANG Jie-Ting;JIAO Can;ZHANG Min-Qiang   

  1. (1 Psychological Application Research Center, South China Normal University, Guangzhou 510631, China)
    (2 Department of Psychology, Shenzhen University, Shenzhen 518000, China)
  • Received:2010-05-04 Revised:1900-01-01 Online:2010-12-15 Published:2010-12-15
  • Contact: ZHANG Min-Qiang

摘要: 潜在类别分析是通过对类别型的外显变量和潜在变量之间的关系建立统计模型, 根据模型参数得到各种潜在类别的具体外在表现的潜在特征分类技术。该分析方法主要应用于心理行为特征的分类、控制认知心理实验中被试个体差异引起的系统误差、评价临床心理诊断的精确性, 以及心理测验中的项目分析、信度分析、结构分析等。对此方法的优劣进行分析比较, 表明:该方法可以与其他测量理论相结合进一步拓展其在心理测量中的应用, 也可在纵向数据和多水平数据中应用。在应用中亦有提升方法技术的空间。

关键词: 潜在类别, 聚类模型, 条件概率, 潜在类别概率

Abstract: Latent class analysis is a statistical technique used to identify subtypes of related cases. In the method, statistic model is built according to relationship between categorical observed and latent variables, and then manifest performances of each latent classes are respectively described based on the related parameters in the model. The analytical approach is mainly used in (1) classification of psychological or behavioral traits; (2) controlling the systematical error of cognitive experiments caused by individual differences; (3) assessing accuracy of clinical psychology diagnostics; (4) analyzing difficulty, discrimination, reliability and structure of psychology measurement. Both strong and weak points are considered, which indicates that, in respect of future development in the psychometric application, the method will be combined with other theoretical frameworks of measurement and also applied to longitudinal and multilevel data. Moreover, the application still sees room for improvement in its methodological technique.

Key words: latent class, cluster model, conditional probability, latent class probability