Approximate Inference for the Factor Loading of a Simple Factor Analysis Model

Authors: Wong, A. C. M.¹; Wu, J.²

Source: Scandinavian Journal of Statistics, Volume 28, Number 2, June 2001 , pp. 407-414(8)

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Abstract:

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.

Keywords: canonical parameter; factor analysis model; signed log likelihood ratio statistic; standardized maximum likelihood departure

Document Type: Original article

DOI: http://dx.doi.org/10.1111/1467-9469.00244

Affiliations: 1: York University, 2: Marquette University

Publication date: 2001-06-01