We consider a latent variable model for multivariate ordinal responses accounting for dependencies among items. Time-dependent latent variables and random effects account for the inter-dependencies of the multivariate ordinal items. Model estimation is usually obtained using the full maximum likelihood via the EM algorithm. However, computationally problems can arise due to the calculation of multiple integrals involved in the likelihood. The paper proposes a pseudolikelihood approach which involves only bivariate marginal probabilities. The proposed estimation method is evaluated by means of a little simulation study. A real data example illustrates the performance of both the full and the limited information estimation method.

A comparison of a pseudo-likelihood estimation and full information maximum likelihood estimation for fitting multivariate longitudinal ordinal data

CAGNONE, SILVIA;
2010

Abstract

We consider a latent variable model for multivariate ordinal responses accounting for dependencies among items. Time-dependent latent variables and random effects account for the inter-dependencies of the multivariate ordinal items. Model estimation is usually obtained using the full maximum likelihood via the EM algorithm. However, computationally problems can arise due to the calculation of multiple integrals involved in the likelihood. The paper proposes a pseudolikelihood approach which involves only bivariate marginal probabilities. The proposed estimation method is evaluated by means of a little simulation study. A real data example illustrates the performance of both the full and the limited information estimation method.
2010
Proceedings of 45th Scientific meeting of the Italian Statistical Society
225
336
Vasdekis V.; Cagnone S.; Moustaki I.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/94319
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