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

Advances in Psychological Science ›› 2017, Vol. 25 ›› Issue (10): 1682-1695.doi: 10.3724/SP.J.1042.2017.01682

• Research Methods • Previous Articles     Next Articles

 Latent variable modeling using Bayesian methods

 WANG Meng-Cheng1,2,3; DENG Qiaowen1,2; BI Xiangyang4   

  1.  (1 Department of Psychology, Guangzhou University; 2 The Center for Psychometric and Latent Variable Modeling, Guangzhou University; 3 The Key Laboratory for Juveniles Mental Health and Educational Neuroscience in Guangdong Province, Guangzhou University, Guangzhou 510006, China) (4 School of Sociology, China University of Political Science and Law, Beijing 102249, China)
  • Received:2016-11-24 Online:2017-10-15 Published:2017-08-13
  • Contact: WANG Meng-Cheng, E-mail: wmcheng2006@126.com; BI Xiangyang, E-mail: necessity@126.com E-mail: E-mail: wmcheng2006@126.com; E-mail: necessity@126.com
  • Supported by:
     

Abstract:  Bayesian statistical methods is one of the two statistic schools. Recently, Bayesian statistical methods are becoming ever more popular in social and behavioral research. However, domestic psychological and behavioral scholars are not familiar with it. We provide an untechnical introduction about Bayesian statistics, particularly in Bayesian method used in latent variable modeling. Specifically, first we compared the difference between Bayesian methods and Frequentist methods in several basic concepts. Thereafter, the Bayes’ Theorem and its analysis procedure were introduced. Finally, to illustrate Bayesian methods in latent variable modeling (i.e., confirmatory factor analysis), a concrete sample was presented. In the end of the paper, we briefly discussed the future direction of Bayesian methods in psychology research.

Key words:  Bayesian, Frequentist methods, latent variable modeling, Mplus

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