Linear latent variable models: the lava-package

Klaus Holst () and Esben Budtz-Jørgensen ()
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Klaus Holst: http://www.biostat.ku.dk/kkho

Computational Statistics, 2013, vol. 28, issue 4, 1385-1452

Abstract: 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. Copyright Springer-Verlag 2013

Keywords: Latent variable model; Structural equation model; R; Maximum likelihood; Serotonin; Seasonality; SERT (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s00180-012-0344-y

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