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Thus, the residuals can be modified to better detect unusual observations. The ratio of the residual to its standard error, called the standardized residual, is
If the residual is standardized with an independent estimate of , the result has a Student's t distribution if the data satisfy the normality assumption. If you estimate by s2(i), the estimate of obtained after deleting the ith observation, the result is a studentized residual:
Observations with | rti|>2 may deserve investigation.
For generalized linear models, the standardized and studentized residuals are
The standardized residuals are stored in variables named
RS_yname and the Studentized residuals are stored
in variables named RT_yname for each response
variable, where yname is the response variable name.
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