Hostname: page-component-8448b6f56d-tj2md Total loading time: 0 Render date: 2024-04-19T21:25:38.561Z Has data issue: false hasContentIssue false
  • English
  • Français

Latent variable models are network models

Published online by Cambridge University Press:  29 June 2010

Peter C. M. Molenaar
Peter C. M. Molenaar
Affiliation:
Department of Human Development and Family Studies, College of Health and Human Development, Pennsylvania State University, University Park, PA 16802. pxm21@psu.eduhttp://www.hhdev.psu.edu/hdfs/faculty/molenaar.html
Get access Rights & Permissions [Opens in a new window]

Abstract

Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 33 , Issue 2-3 , June 2010 , pp. 166
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Molenaar, P. C. M. (2003) State space techniques in structural equation modeling: Transformation of latent variables in and out of latent variable models. Unpublished manuscript, University of Amsterdam. Available at: http://www.hhdev.psu.edu/hdfs/faculty/docs/StateSpaceTechniques.pdf.Google Scholar
Molenaar, P. C. M., van, Rijn, P. & Hamaker, E. (2007) A new class of SEM model equivalences and its implications. Data analytic techniques for dynamical systems, ed. Boker, S. M. & Wenger, M. J., pp. 189–211. Erlbaum.Google Scholar