, Volume 69, Issue 1, pp 101–122

An EM algorithm for fitting two-level structural equation models

Theory And Methods

DOI: 10.1007/BF02295842

Cite this article as:
Liang, J. & Bentler, P.M. Psychometrika (2004) 69: 101. doi:10.1007/BF02295842


Maximum likelihood is an important approach to analysis of two-level structural equation models. Different algorithms for this purpose have been available in the literature. In this paper, we present a new formulation of two-level structural equation models and develop an EM algorithm for fitting this formulation. This new formulation covers a variety of two-level structural equation models. As a result, the proposed EM algorithm is widely applicable in practice. A practical example illustrates the performance of the EM algorithm and the maximum likelihood statistic.

Key words

Chi-square statisticmean and covariance structuresEM algorithmmaximum likelihoodmultivariate normal distributiontwo-level structural equation models

Copyright information

© The Psychometric Society 2004

Authors and Affiliations

  1. 1.School of BusinessUniversity of New HavenUSA
  2. 2.Department of PsychologyUniversity of California, Los AngelesLos Angeles