DFFITS

DFFITS is a diagnostic meant to show how influential a point is in a statistical regression. It was proposed in the 1980 book Regression Diagnostics: Identifying Influential Data and Sources of Collinearity by David Belsley, Edwin Kuh, and Roy Welsch. It is defined as the change ("DFFIT"), in the predicted value for a point, obtained when that point is left out of the regression, "Studentized" by dividing by the estimated standard deviation of the fit at that point:
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Several measures have been given for testing for leverage and influence of a specific case in regression (including studentized residuals , studentized deleted residuals , DFFITS, and standardized DFFITS ). Belsley et al. (1980) have suggested DFFITS, a measure which gives greater weight to outlying observations than Cook's distance . The formula for DFFITS is

where
ei is the error for the ith case
hi is the leverage for the ith case and

For more information see Hocking (1996) and Ryan (1997).

This is another measure of impact of the respective case on the regression equation. The formula for standardized DFFITS is

where hi is the leverage for the ith case
and

See also, DFFITS, studentized residuals, and studentized deleted residuals. For more information see Hocking (1996) and Ryan (1997).