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Approximate Inference for the Factor Loading of a Simple Factor Analysis Model
Author(s) -
Wong A. C. M.,
Wu J.
Publication year - 2001
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/1467-9469.00244
Subject(s) - mathematics , inference , factor (programming language) , statistic , simple (philosophy) , measure (data warehouse) , statistics , factor analysis , likelihood ratio test , maximum likelihood , computer science , data mining , artificial intelligence , philosophy , epistemology , programming language
We study a factor analysis model with two normally distributed observations and one factor. Two approximate conditional inference procedures for the factor loading are developed. The first proposal is a very simple procedure but it is not very accurate. The second proposal gives extremely accurate results even for very small sample size. Moreover, the calculations require only the signed log‐likelihood ratio statistic and a measure of the standardized maximum likelihood departure. Simulations are used to study the accuracy of the proposed procedures.