A Class of Factor Analysis Estimation Procedures with Common Asymptotic Sampling Properties
- 1 September 1975
- journal article
- Published by Cambridge University Press (CUP) in Psychometrika
- Vol. 40 (3) , 315-335
- https://doi.org/10.1007/bf02291761
Abstract
A general class of estimation procedures for the factor model is considered. The procedures are shown to yield estimates possessing the same asymptotic sampling properties as those from estimation by maximum likelihood or generalized least squares, both of which are special members of the class. General expressions for the derivatives needed for Newton-Raphson determination of the estimates are derived. Numerical examples are given, and the effect of the choice of estimation procedure is discussed.Keywords
This publication has 12 references indexed in Scilit:
- A Note on Lawley’s Formulas for Standard Errors in Maximum Likelihood Factor AnalysisPsychometrika, 1973
- Linear Statistical Inference and its ApplicationsPublished by Wiley ,1973
- The Variance Information Manifold and the Functions on ItPublished by Elsevier ,1973
- A RAPIDLY CONVERGENT METHOD FOR MAXIMUM‐LIKELIHOOD FACTOR ANALYSISBritish Journal of Mathematical and Statistical Psychology, 1970
- A Newton-Raphson Algorithm for Maximum Likelihood Factor AnalysisPsychometrika, 1969
- A Comparison of Factor Analytic TechniquesPsychometrika, 1968
- Some Contributions to Maximum Likelihood Factor AnalysisPsychometrika, 1967
- XX.—Some New Results in Maximum Likelihood Factor AnalysisProceedings of the Royal Society of Edinburgh. Section A. Mathematical and Physical Sciences, 1967
- Large-Sample Theory: Parametric CaseThe Annals of Mathematical Statistics, 1956
- VI.—The Estimation of Factor Loadings by the Method of Maximum LikelihoodProceedings of the Royal Society of Edinburgh, 1940