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Latent variable models for multivariate longitudinal ordinal responses
Author(s) -
Cag Silvia,
Moustaki Irini,
Vasdekis Vassilis
Publication year - 2009
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1348/000711008x320134
Subject(s) - latent variable , multivariate statistics , latent variable model , autoregressive model , mathematics , ordinal data , ordinal regression , statistics , econometrics , variable (mathematics) , set (abstract data type) , computer science , mathematical analysis , programming language
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.