Prediction in linear mixed models

A - Papers appearing in refereed journals

Welham, S. J., Cullis, B. R., Gogel, B., Gilmour, A. and Thompson, R. 2004. Prediction in linear mixed models. Australian & New Zealand Journal of Statistics. 46 (3), pp. 325-347.

AuthorsWelham, S. J., Cullis, B. R., Gogel, B., Gilmour, A. and Thompson, R.

Following estimation of effects from a linear mixed model, it is often useful to form predicted values for certain factor/variate combinations. The process has been well defined for linear models, but the introduction of random effects into the model means that a decision has to be made about the inclusion or exclusion of random model terms from the predictions. This paper discusses the interpretation of predictions formed including or excluding random terms. Four datasets are used to illustrate circumstances where different prediction strategies may be appropriate: in an orthogonal design, an unbalanced nested structure, a model with cubic smoothing spline terms and for kriging after spatial analysis. The examples also show the need for different weighting schemes that recognize nesting and aliasing during prediction, and the necessity of being able to detect inestimable predictions.

KeywordsStatistics & Probability
Year of Publication2004
JournalAustralian & New Zealand Journal of Statistics
Journal citation46 (3), pp. 325-347
Digital Object Identifier (DOI)
Open accessPublished as non-open access
Funder project or code445
Research in statistics relevant to biological processes
Output statusPublished
Publication dates
Online10 Sep 2004
Publication process dates
Accepted01 Jun 2003
Copyright licensePublisher copyright

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