Linear latent variable models: the lava-package
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features are implemented including robust standard errors for clustered correlated data, multigroup analyses, non-linear parameter constraints, inference with incomplete data, maximum likelihood estimation with censored and binary observations, and instrumental variable estimators. In addition an extensive simulation interface covering a broad range of non-linear generalized structural equation models is described. The model and software are demonstrated in data of measurements of the serotonin transporter in the human brain.
Originalsprog | Engelsk |
---|---|
Tidsskrift | Computational Statistics |
Vol/bind | 28 |
Udgave nummer | 4 |
Sider (fra-til) | 1385-1452 |
Antal sider | 68 |
ISSN | 0943-4062 |
DOI | |
Status | Udgivet - 1 aug. 2013 |
ID: 117204927