Efficient Estimation in Image Factor Analysis

Karl G. Jöreskog

47 citations0/0 files storedPsychometrika

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Psychometric Methodologies and Testing Statistical Methods and Applications Statistical Methods and Bayesian Inference

Abstract

The image factor analytic model (IFA), as related to Guttman’s image theory, is considered as an alternative to the traditional factor analytic model (TFA). One advantage with IFA, as compared with TFA, is that more factors can be extracted without yielding a perfect fit to the observed data. Several theorems concerning the structural properties of IFA are proved and an iterative procedure for finding the maximum likelihood estimates of the parameters of the IFA-model is given. Substantial experience with this method verifies that Heywood cases never occur. Results of an artificial experiment suggest that IFA may be more factorially invariant than TFA under selection of tests from a large battery.

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References

1954Some Necessary Conditions for Common-Factor Analysis 1965Problems in Measuring Change 1961Modern Factor Analysis.1967Some Contributions to Maximum Likelihood Factor Analysis 1962Factor Analysis as a Statistical Method 1965Alpha Factor Analysis 1940VI.—The Estimation of Factor Loadings by the Method of Maximum Likelihood 1952Psychometric Monographs

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