DFBETA for Outlier Analysis | Regression diagnostics in STATA (11)

The dfbeta is used to help identify individual observations that are having an unusually high influence on your model. It is suggested by Belsley, Kuh, and Welsch (1980) that you should look closely at observations where the dfbeta is greater than 2 divided by the square root of N (total number of observations).
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