Latent Variable Growth Modeling with Multilevel Data

  • Bengt Muthén
Part of the Lecture Notes in Statistics book series (LNS, volume 120)


Growth modeling of multilevel data is presented within a latent variable framework that allows analysis with conventional structural equation modeling software. Latent variable modeling of growth considers a vector of observations over time for an individual, reducing the two-level problem to a one-level problem Analogous to this, three-level data on students, time points, and schools can be modeled by a two-level growth model. An interesting feature of this two-level model is that contrary to recent applications of multilevel latent variable modeling, a mean structure is imposed in addition to the covariance structure. An example using educational achievement data illustrates the methodology.


Simple Random Sample Latent Variable Modeling Covariance Structure Analysis Multilevel Data Growth Score 
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Copyright information

© Springer-Verlag New York, Inc. 1997

Authors and Affiliations

  • Bengt Muthén
    • 1
  1. 1.Graduate School of Education & Information StudiesUniversity of California, Los AngelesLos AngelesUSA

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