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Detection of outlier based on standardized Pearson residuals
has gained widespread use in logistic regression model in the presence of a
single outlier. An innovation attempts in the same direction but dealing for
a group of outliers have been made using generalized standardized Pearson residual
which requires a graphical or a robust estimator to find suspected outliers
to form a group deletion. In this study, an alternative measure namely modified
standardized Pearson residual is derived from the robust logistic diagnostic.
The weakness of standardized Pearson residuals and the usefulness of generalized
standardized Pearson residual and modified standardized Pearson residual are
examined through several real examples and Monte Carlo simulation study. The
results of this study signify that the generalized standardized Pearson residual
and the modified standardized Pearson residual perform equally good in identifying
a group of outliers.
