, Volume 44, Issue 4, pp 409–420 | Cite as

Estimation for the multiple factor model when data are missing

  • Carl Finkbeiner


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.

Key words

factor analysis missing data 


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Reference notes

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Copyright information

© The Psychometric Society 1979

Authors and Affiliations

  • Carl Finkbeiner
    • 1
  1. 1.Invorydale Technical Center, 3W76The Procter & Gamble Co.Cincinnati

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