Deletion diagnostics for the linear mixed model
Citation:
Dominic Mark Dillane, 'Deletion diagnostics for the linear mixed model', [thesis], Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2006, pp 146Download Item:

Abstract:
Modeling data is an integral element of modern statistical analysis. Methodological
developments combined with the explosion in computing power over the past ten to
fifteen years have greatly enhanced statisticians' ability to model situations and
phenomena. The need to assess a model's validity and suitability is an integral element
of the model building process. Model criticism is central to this thesis and specifically
model criticism for one of the most frequently utilised models in statistical analyses, the
Linear Mixed Model with normally distributed errors. Particular emphasis is given to
deletion diagnostics for both the fixed and for the covariance structure parameters.
Author: Dillane, Dominic Mark
Advisor:
Haslett, JohnQualification name:
Doctor of Philosophy (Ph.D.)Publisher:
Trinity College (Dublin, Ireland). School of Computer Science & StatisticsNote:
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thesisAvailability:
Full text availableKeywords:
Statistics, Ph.D., Ph.D. Trinity College DublinLicences: