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A note on deletion diagnostics for estimating equations


  • John S. Preisser
  • Bahjat F. Qaqish
  • Jamie Perin


We describe an algorithm based upon the Sherman--Morrison--Woodbury formula for the inversion of matrices with special structure that occur in formulae for deletion diagnostics. Substantial computational savings relative to a method based upon Cholesky's decomposition are illustrated. The result has broad application to regression diagnostics for clustered data. Copyright 2008, Oxford University Press.

Suggested Citation

  • John S. Preisser & Bahjat F. Qaqish & Jamie Perin, 2008. "A note on deletion diagnostics for estimating equations," Biometrika, Biometrika Trust, vol. 95(2), pages 509-513.
  • Handle: RePEc:oup:biomet:v:95:y:2008:i:2:p:509-513

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    Cited by:

    1. Vens, Maren & Ziegler, Andreas, 2012. "Generalized estimating equations and regression diagnostics for longitudinal controlled clinical trials: A case study," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1232-1242.

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