Choosing the number of factors in factor analysis with incomplete data via a novel hierarchical Bayesian information criterion

doi:10.1007/s11634-024-00582-w

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Status	已发表Published
Title	Choosing the number of factors in factor analysis with incomplete data via a novel hierarchical Bayesian information criterion
Creator	Zhao, Jianhua 1; Shang, Changchun 1,2; Li, Shulan 3; Xin, Ling4 ; Yu, Philip L.H.5
Date Issued	2025-03-01
Source Publication	Advances in Data Analysis and Classification
ISSN	1862-5347
Volume	19 Issue:1 Pages:209-235
Abstract	The Bayesian information criterion (BIC), defined as the observed data log likelihood minus a penalty term based on the sample size N, is a popular model selection criterion for factor analysis with complete data. This definition has also been suggested for incomplete data. However, the penalty term based on the ‘complete’ sample size N is the same no matter whether in a complete or incomplete data case. For incomplete data, there are often only N
Keyword	BIC Factor analysis Incomplete data Maximum likelihood Model selection Variational Bayesian
DOI	10.1007/s11634-024-00582-w
URL	View source
Indexed By	SCIE
Language	英语English
WOS Research Area	Mathematics
WOS Subject	Statistics & Probability
WOS ID	WOS:001176554300001
Scopus ID	2-s2.0-105001585927
Citation statistics
Document Type	Journal article
Identifier	http://repository.uic.edu.cn/handle/39GCC9TT/12824
Collection	Faculty of Busines and Management
Corresponding Author	Zhao, Jianhua
Affiliation	1.School of Statistics and Mathematics,Yunnan University of Finance and Economics,Kunming,355 Longquan road,650221,China 2.School of Mathematics and Statistics,Guilin University of Technology,Guilin,541004,China 3.School of Accounting,Yunnan University of Finance and Economics,Kunming,650221,China 4.Division of Business and Management,BNU-HKBU United International College,Zhuhai,519087,China 5.Department of Mathematics and Information Technology,The Education University of Hong Kong,Hong Kong
Recommended Citation GB/T 7714	Zhao, Jianhua,Shang, Changchun,Li, Shulanet al. Choosing the number of factors in factor analysis with incomplete data via a novel hierarchical Bayesian information criterion[J]. Advances in Data Analysis and Classification, 2025, 19(1): 209-235.
APA	Zhao, Jianhua, Shang, Changchun, Li, Shulan, Xin, Ling, & Yu, Philip L.H. (2025). Choosing the number of factors in factor analysis with incomplete data via a novel hierarchical Bayesian information criterion. Advances in Data Analysis and Classification, 19(1), 209-235.
MLA	Zhao, Jianhua,et al."Choosing the number of factors in factor analysis with incomplete data via a novel hierarchical Bayesian information criterion". Advances in Data Analysis and Classification 19.1(2025): 209-235.

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