Robust linear mixed models using the skew t distribution with application to schizophrenia data.

06:00 EDT 4th August 2010 | BioPortfolio

Summary of "Robust linear mixed models using the skew t distribution with application to schizophrenia data."

We consider an extension of linear mixed models by assuming a multivariate skew t distribution for the random effects and a multivariate t distribution for the error terms. The proposed model provides flexibility in capturing the effects of skewness and heavy tails simultaneously among continuous longitudinal data. We present an efficient alternating expectation-conditional maximization (AECM) algorithm for the computation of maximum likelihood estimates of parameters on the basis of two convenient hierarchical formulations. The techniques for the prediction of random effects and intermittent missing values under this model are also investigated. Our methodologies are illustrated through an application to schizophrenia data.


Department of Applied Mathematics, National Chung Hsing University, Taichung 402, Taiwan.

Journal Details

This article was published in the following journal.

Name: Biometrical journal. Biometrische Zeitschrift
ISSN: 1521-4036


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Relevant Topics

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Psychiatry is the study of mental disorders and their diagnosis, management and prevention.  Conditions include schizophrenia, severe depression and panic disorders among others. There are pharmaceutical treatments as well as other therapies to help...

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