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Structural Equation Modeling: A Multidisciplinary Journal Volume 8, 2001 - Issue 1
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Original Articles

A Primer on Maximum Likelihood Algorithms Available for Use With Missing Data

Craig K. Enders
Pages 128-141 | Published online: 19 Nov 2009
 
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Abstract

Maximum likelihood algorithms for use with missing data are becoming commonplace in microcomputer packages. Specifically, 3 maximum likelihood algorithms are currently available in existing software packages: the multiple-group approach, full information maximum likelihood estimation, and the EM algorithm. Although they belong to the same family of estimator, confusion appears to exist over the differences among the 3 algorithms. This article provides a comprehensive, nontechnical overview of the 3 maximum likelihood algorithms. Multiple imputation, which is frequently used in conjunction with the EM algorithm, is also discussed.

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