A structural modeling approach to a multilevel random coefficients model

Michael J. Rovine, Peter C.M. Molenaar

Research output: Contribution to journalArticlepeer-review

74 Scopus citations


A method for estimating the random coefficients model using covariance structure modeling is presented. This method allows one to estimate both fixed and random effects. A way of translating the general linear mixed model into a structural equation modeling (SEM) format is presented. In particular, a LISREL setup for the multiple group linear latent growth curve model is illustrated with suggestions on ways to parameterize more complex models. To illustrate the procedure, we apply the method to both simulated and real data. The method is shown to recover the simulated parameter values. Results and interpretation for the Belsky and Rovine (1990) marriage data are presented. Other applications of the more general model are suggested.

Original languageEnglish (US)
Pages (from-to)51-88
Number of pages38
JournalMultivariate Behavioral Research
Issue number1
StatePublished - 2000

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)


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