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multiple and conditional deletion diagnostics for general linear models
Authors:Ingrid A Baade  Anthony N Pettitt
Institution:School of Mathematical Sciences , Queensland University of Technology , Queensland, 4001, Australia
Abstract:In this paper we develop multiple case deletion statistics for the general linear model so that a residual vector and a leverage matrix are identified which have roles analogous to residuals and leverage for ordinary least squares models. We extend the notion of the conditional deletion diagnostic to general linear models. The residuals, leverage and deletion diagnostics are illustrated with data modelled by a linear growth curve.
Keywords:Cook's distance  correlated errors  generalised least squares  in¬fluence  leverage  one-step approximation  residual
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