Journal
BIOMETRICS
Volume 61, Issue 3, Pages 684-691Publisher
WILEY
DOI: 10.1111/j.1541-0420.2005.00354.x
Keywords
bias; estimating functions; longitudinal data; M-estimation; robust estimation
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Robust methods are useful in making reliable statistical inferences when there are small deviations from the model assumptions. The widely used method of the generalized estimating equations can be robustified by replacing the standardized residuals with the M-residuals. If the Pearson residuals are assumed to be unbiased from zero, parameter estimators from the robust approach are asymptotically biased when error distributions are not symmetric. We propose a distribution-free method for correcting this bias. Our extensive numerical studies show that the proposed method can reduce the bias substantially. Examples are given for illustration.
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