A variance shift model for detection of outliers in the linear mixed model

A - Papers appearing in refereed journals

Gumedze, F. N., Welham, S. J., Gogel, B. J. and Thompson, R. 2010. A variance shift model for detection of outliers in the linear mixed model. Computational Statistics & Data Analysis. 54 (9), pp. 2128-2144.

AuthorsGumedze, F. N., Welham, S. J., Gogel, B. J. and Thompson, R.
Abstract

A variance shift outlier model (VSOM), previously used for detecting outliers in the linear model, is extended to the variance components model. This VSOM accommodates outliers as observations with inflated variance, with the status of the th observation as an outlier indicated by the size of the associated shift in the variance. Likelihood ratio and score test statistics are assessed as objective measures for determining whether the th observation has inflated variance and is therefore an outlier. It is shown that standard asymptotic distributions do not apply to these tests for a VSOM, and a modified distribution is proposed. A parametric bootstrap procedure is proposed to account for multiple testing. The VSOM framework is extended to account for outliers in random effects and is shown to have an advantage over case-deletion approaches. A simulation study is presented to verify the performance of the proposed tests. Challenges associated with computation and extensions of the VSOM to the general linear mixed model with correlated errors are discussed.

KeywordsLikelihood ratio test; Linear mixed model; Multiple testing; Outlier detection; REML; Score test; Variance shift outlier model
Year of Publication2010
JournalComputational Statistics & Data Analysis
Journal citation54 (9), pp. 2128-2144
Digital Object Identifier (DOI)doi:10.1016/j.csda.2010.03.019
Open accessPublished as non-open access
Funder project or codeCentre for Mathematical and Computational Biology (MCB)
Development and extensions of linear mixed models
Output statusPublished
Publication dates
Online28 Mar 2010
Publication process dates
Accepted22 Mar 2010
Copyright licensePublisher copyright
ISSN0167-9473
PublisherElsevier Science Bv

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