Latent variable models for multivariate longitudinal ordinal responses

Publication type

Journal Article

Authors

Publication date

June 1, 2009

Abstract:

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 v/ithin 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 fector. 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.

Published in

British Journal of Mathematical and Statistical Psychology

Volume

Volume: 62 (2): 401-415

DOI

http://dx.doi.org/10.1348/000711008X320134

Subjects

Notes

Albert Sloman Library Periodicals *restricted to Univ. Essex registered users*

#513235

News

Latest findings, new research

Publications search

Search all research by subject and author

Podcasts

Researchers discuss their findings and what they mean for society

Projects

Background and context, methods and data, aims and outputs

Events

Conferences, seminars and workshops

Survey methodology

Specialist research, practice and study

Taking the long view

ISER's annual report

Themes

Key research themes and areas of interest