Use of the score test as a goodness-of-fit measure of the covariance structure in genetic analysis of longitudinal data

A - Papers appearing in refereed journals

Jaffrezic, F., White, I. M. S. and Thompson, R. 2003. Use of the score test as a goodness-of-fit measure of the covariance structure in genetic analysis of longitudinal data. Genetics Selection Evolution. 35, pp. 185-198.

AuthorsJaffrezic, F., White, I. M. S. and Thompson, R.
Abstract

Model selection is an essential issue in longitudinal data analysis since many different models have been proposed to fit the covariance structure. The likelihood criterion is commonly used and allows to compare the fit of alternative models. Its value does not reflect, however, the potential improvement that can still be reached in fitting the data unless a reference model with the actual covariance structure is available. The score test approach does not require the knowledge of a reference model, and the score statistic has a meaningful interpretation in itself as a goodness-of-fit measure. The aim of this paper was to show how the score statistic may be separated into the genetic and environmental parts, which is difficult with the likelihood criterion, and how it can be used to check parametric assumptions made on variance and correlation parameters. Selection of models for genetic analysis was applied to a dairy cattle example for milk production.

Keywordsgenetic longitudinal data analysis; score test; goodness-of-fit measure; covariance structure
Year of Publication2003
JournalGenetics Selection Evolution
Journal citation35, pp. 185-198
Digital Object Identifier (DOI)doi:10.1051/gse:2003003
Open accessPublished as ‘gold’ (paid) open access
Funder project or code445
513
Research in statistics relevant to biological processes
Publisher's version
Output statusPublished
Publication dates
Online15 Mar 2003
Publication process dates
Accepted07 Aug 2002
Copyright licenseCC BY
PublisherBiomed Central Ltd
ISSN0999-193X

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