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The detection of residual serial correlation in linear mixed models

✍ Scribed by Geert Verbeke; Emmanuel Lesaffre; Larry J. Brant

Publisher
John Wiley and Sons
Year
1998
Tongue
English
Weight
146 KB
Volume
17
Category
Article
ISSN
0277-6715

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✦ Synopsis

described how the empirical semi-variogram of ordinary least squares residuals can be used to suggest an appropriate serial correlation structure in stationary linear mixed models. In this paper, this approach is extended to non-stationary models which include random effects other than intercepts, and will be applied to prostate cancer data, taken from the Baltimore Longitudinal Study of Aging. A simulation study demonstrates the effectiveness of this extended variogram for improving the covariance structure of the linear mixed model used to describe the prostate data.

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