Estimation for the Multiple Factor Model when Data are Missing
- 1 December 1979
- journal article
- Published by Cambridge University Press (CUP) in Psychometrika
- Vol. 44 (4) , 409-420
- https://doi.org/10.1007/bf02296204
Abstract
A maximum likelihood method of estimating the parameters of the multiple factor model when data are missing from the sample is presented. A Monte Carlo study compares the method with 5 heuristic methods of dealing with the problem. The present method shows some advantage in accuracy of estimation over the heuristic methods but is considerably more costly computationally.Keywords
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