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Latent Variable Modelling: A Survey

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Author Info
ANDERS SKRONDAL
SOPHIA RABE-HESKETH

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Abstract

Latent variable modelling has gradually become an integral part of mainstream statistics and is currently used for a multitude of applications in different subject areas. Examples of 'traditional' latent variable models include latent class models, item-response models, common factor models, structural equation models, mixed or random effects models and covariate measurement error models. Although latent variables have widely different interpretations in different settings, the models have a very similar mathematical structure. This has been the impetus for the formulation of general modelling frameworks which accommodate a wide range of models. Recent developments include multilevel structural equation models with both continuous and discrete latent variables, multiprocess models and nonlinear latent variable models. Copyright 2007 Board of the Foundation of the Scandinavian Journal of Statistics..

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9469.2007.00573.x
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Publisher Info
Article provided by Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association and Swedish Statistical Association in its journal Scandinavian Journal of Statistics.

Volume (Year): 34 (2007)
Issue (Month): 4 ()
Pages: 712-745
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Handle: RePEc:bla:scjsta:v:34:y:2007:i:4:p:712-745

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  1. Sophia Rabe-Hesketh, 2007. "Multilevel modeling of complex survey data," West Coast Stata Users' Group Meetings 2007 14, Stata Users Group. [Downloadable!]
    Other versions:
  2. Lynda G. Gagné & Ana Ferrer, 2006. "Housing, Neighbourhoods and Development Outcomes of Children in Canada," Canadian Public Policy, University of Toronto Press, vol. 32(3), pages 275-300, September. [Downloadable!] (restricted)
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