Skip to main content
SpringerLink
Log in

A Multilevel Latent Variable Model for Multidimensional Longitudinal Data

  • Conference paper
  • First Online:
Data Analysis and Classification

  • 1542 Accesses

Abstract

We propose a latent variable approach for modeling repeated multiple continuous responses. First the item correlation over time is explained by using latent growth curves, then the variability among items is accounted for by an overall latent variable. An EM algorithm is implemented to obtain maximum likelihood estimation of the model parameters.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Bollen, K. A., & Curran, P. J. (2006). Latent Curve Models: a structural equation perspective. New Jersey: Wiley Series in Probability and Statistics.

    MATH  Google Scholar 

  • Goldstein, H. (2003). Multilevel statistical models. Kendalls Library of Statics. London: Arnold.

    MATH  Google Scholar 

  • Jöreskog, K., & Sörbom, D. (2001). LISREL 8: Users’ reference guide. Chicago: SSI.

    Google Scholar 

  • Stroud, A., & Secrest, D. (1966). Gaussian quadrature formulas. Englewood Cliffs, NJ: Prentice-Hall.

    MATH  Google Scholar 

  • Skrondal, A., & Rabe-Heskett, S. (2004). Generalized latent variable modeling: multilevel, longitudinal, and structural equation models. Boca Raton, FL: Chapman and Hall/CRC.

    Book  MATH  Google Scholar 

  • Dunson, D. B. (2003). Dynamic latent trait models for multidimensional longitudinal data. Journal of American Statistical Association,98(4), 555–563.

    Article  MATH  MathSciNet  Google Scholar 

  • Roy, J., & Lin, X. (2000). Latent variable models for longitudinal data with multiple continuous outcomes. Biometrics,56(4), 1047–1054.

    Article  MATH  MathSciNet  Google Scholar 

  • Wheaton, B., Muthén, M., Alwin, D. F., & Summers, G. F. (1977). Assessing reliability and stability in panel models. Sociological Methodology,8, 84–136.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Statistics, University of Bologna, Via Belle Arti, 41, 40126, Bologna, Italy

    Silvia Bianconcini

Authors
  1. Silvia Bianconcini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Silvia Cagnone
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Silvia Bianconcini .

Editor information

Editors and Affiliations

  1. Fac. Economia, Università Macerata, Via Crescimbeni 20, Macerata, 62100, Italy

    Francesco Palumbo

  2. Dipto. Matematica e Statistica, Università Federico II di Napoli, Via Cinthia (Monte S. Angelo), Napoli, 80126, Italy

    Carlo Natale Lauro

  3. Depto. Economía y Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas 25-27, Barcelona, 08005, Spain

    Michael J. Greenacre

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bianconcini, S., Cagnone, S. (2010). A Multilevel Latent Variable Model for Multidimensional Longitudinal Data. In: Palumbo, F., Lauro, C., Greenacre, M. (eds) Data Analysis and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03739-9_37

Download citation

Publish with us

Policies and ethics

Search

Navigation