New Developments in Latent Variable Models: Non-linear and Dynamic Models

Irini Moustaki ()
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Irini Moustaki: London School of Economics and Political Science Department of Statistics

A chapter in COMPSTAT 2008, 2008, pp 155-164 from Springer

Abstract: Abstract The paper reviews recent work on latent variable models for ordinal longitudinal variables and factor models with non-linear terms. The model for longitudinal data has been recently proposed by Cagnone, Moustaki and Vasdekis (2008). The model allows for time-dependent latent variables to explain the associations among ordinal variables within time where the associations among the same items across time are modelled with item-specific random effects. Rizopoulos and Moustaki (2007) extended the generalized latent variable model framework to allow for non-linear terms (interactions and higher order terms). Both models are estimated with full information maximum likelihood. Computational aspects, goodness-of-fit statistics and an application are presented.

Keywords: latent variable models; ordinal data; longitudinal data; non-linear terms (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2084-3_13

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DOI: 10.1007/978-3-7908-2084-3_13

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