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Biometrika 1996 83(3):551-562; doi:10.1093/biomet/83.3.551
© 1996 by Biometrika Trust
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Deletion diagnostics for generalised estimating equations

JOHN S. PREISSER1 and BAHJAT F. QAQISH2

1Section on Biostatistics, Bowman Gray School of Medicine, Medical Center Boulevard Winston-Salem, North Carolina 27157–1063, U.S.A
2Department of Biostatistics, School of Public Health University of North Carolina Chapel Hill, North Carolina 27599–7400, U.S.A

Deletion diagnostics are proposed for generalised estimating equations. The diagnostics consider leverage and residuals to measure the influence of a subset of observations on the estimated regression parameters and on the estimated values of the linear predictor. Computational formulae are provided which correspond to the influence of a single observation and of an entire cluster of correlated observations. Additionally, diagnostics are given which approximate the effect of deletion of an arbitrary subset of observations under a model with general covariance structure and arbitrary link function, extending Proposition 3 of Christensen, Pearson & Johnson (1992). The proposed measures are applied to medical data.

Key Words: Cook's distance • Generalised estimating equations • Generalised linear model • Influence • Leverage • One-step approximation • Regression diagnostics • Residual


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