An approximation of a multivariative stochastic model for the analysis of longitudinal data

We propose to approximate a model for multivariate repeated measures that incorporated random effects, correlated stochastic process and measurements error. The model is generalization for univariate longitudinal data given by Taylor et al. (1994). The stochastic process used in this paper is the mu...

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Main Authors: Abu Bakar, Mohd Rizam, Ali Salah, Khalid
Format: Article
Language:English
English
Published: European Journals, Inc. 2008
Online Access:http://psasir.upm.edu.my/id/eprint/7030/1/An%20approximation%20of%20a%20multivariative%20stochastic%20model%20for%20the%20analysis%20of%20longitudinal%20data.pdf
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author Abu Bakar, Mohd Rizam
Ali Salah, Khalid
author_facet Abu Bakar, Mohd Rizam
Ali Salah, Khalid
author_sort Abu Bakar, Mohd Rizam
collection UPM
description We propose to approximate a model for multivariate repeated measures that incorporated random effects, correlated stochastic process and measurements error. The model is generalization for univariate longitudinal data given by Taylor et al. (1994). The stochastic process used in this paper is the multivariate Integrated Omstein-Uhlenbeck (IOU) process. We consider a Bayesian approach which is motivated by the complexity of the model, thus, we propose to approximate the IOU stochastic process in a simple way that will mitigate the necessity to invert the stochastic process covariance matrix separately for each group at each iteration of the Markov Chain Monte Carlo (MCMC) sampler. The proposed method is illustrated by application to the melanoma data set.
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spelling upm.eprints-70302015-12-07T06:50:25Z http://psasir.upm.edu.my/id/eprint/7030/ An approximation of a multivariative stochastic model for the analysis of longitudinal data Abu Bakar, Mohd Rizam Ali Salah, Khalid We propose to approximate a model for multivariate repeated measures that incorporated random effects, correlated stochastic process and measurements error. The model is generalization for univariate longitudinal data given by Taylor et al. (1994). The stochastic process used in this paper is the multivariate Integrated Omstein-Uhlenbeck (IOU) process. We consider a Bayesian approach which is motivated by the complexity of the model, thus, we propose to approximate the IOU stochastic process in a simple way that will mitigate the necessity to invert the stochastic process covariance matrix separately for each group at each iteration of the Markov Chain Monte Carlo (MCMC) sampler. The proposed method is illustrated by application to the melanoma data set. European Journals, Inc. 2008 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/7030/1/An%20approximation%20of%20a%20multivariative%20stochastic%20model%20for%20the%20analysis%20of%20longitudinal%20data.pdf Abu Bakar, Mohd Rizam and Ali Salah, Khalid (2008) An approximation of a multivariative stochastic model for the analysis of longitudinal data. European Journal of Scientific Research, 20 (1). pp. 76-87. ISSN 1450-216X http://www.eurojournals.com/ English
spellingShingle Abu Bakar, Mohd Rizam
Ali Salah, Khalid
An approximation of a multivariative stochastic model for the analysis of longitudinal data
title An approximation of a multivariative stochastic model for the analysis of longitudinal data
title_full An approximation of a multivariative stochastic model for the analysis of longitudinal data
title_fullStr An approximation of a multivariative stochastic model for the analysis of longitudinal data
title_full_unstemmed An approximation of a multivariative stochastic model for the analysis of longitudinal data
title_short An approximation of a multivariative stochastic model for the analysis of longitudinal data
title_sort approximation of a multivariative stochastic model for the analysis of longitudinal data
url http://psasir.upm.edu.my/id/eprint/7030/1/An%20approximation%20of%20a%20multivariative%20stochastic%20model%20for%20the%20analysis%20of%20longitudinal%20data.pdf
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