A SAS/IML software program for GEE and regression diagnostics

Authors:
Bradley G. Hammill;John S. Preisser
Affiliations:
Duke Clinical Research Institute, Duke University, Durham, NC, USA;Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Venue:
Computational Statistics & Data Analysis
Year:
2006

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Abstract

A SAS/IML software program is described that computes regression diagnostics for generalized estimating equations. These diagnostics are computationally efficient and accurate approximations for the effect of deleting one observation or one cluster on individual regression coefficients (DFBETA) or on the overall fit of the model (Cook's Distance). New formulae for the diagnostics are presented which are equivalent to those introduced by Preisser and Qaqish [1996. Deletion diagnostics for generalised estimating equations. Biometrika 83, 551-562]. The new formulae expose the relationships of the diagnostic measures to the GEE score equations and to a bias-corrected GEE variance estimator which is also implemented in the SAS macro. The macro is applied to three clustered data sets.