Structural equation models with latent variables
AbstractThis talk will introduce the main ideas of structural equation models (SEMs) with latent variables and Stata tools that can be used for such models. The two approaches most often used in the applied work are numeric integration of the latent variables and covariance structure modeling. The first approach is implemented in Stata via -gllamm- (developed by Sophia Rabe-Hesketh). The second approach is currently implemented in -confa- for confirmatory factor analysis models. Also, introduction of the generalized method of moments (GMM) estimation and testing framework in version 11 of Stata made it possible to estimate SEMs by using moderately complex parameter and matrix manipulations. Working examples will be provided with some popular data sets (Holzinger-Swineford factor analysis model and Bollen's industrialization and political democracy model).
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Stata Users Group in its series BOS10 Stata Conference with number 7.
Date of creation: 20 Jul 2010
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-07-31 (All new papers)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F Baum).
If references are entirely missing, you can add them using this form.