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Latent variable models for multivariate longitudinal ordinal responses

By Silvia Cagnone, Irini Moustaki and Vassilis Vasdekis


The paper proposes a full information maximum likelihood estimation method for modelling multivariate longitudinal ordinal variables. Two latent variable models are proposed that account for dependencies among items within time and between time. One model fits item-specific random effects which account for the between time points correlations and the second model uses a common factor. The relationships between the time-dependent latent variables are modelled with a non-stationary autoregressive model. The proposed models are fitted to a real data set

Topics: QA Mathematics
Publisher: Wiley-Blackwell on behalf of the British Psychological Society
Year: 2009
DOI identifier: 10.1348/000711008X320134
OAI identifier:
Provided by: LSE Research Online
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