Binary Logistic Regression

Unusual Observations Table - Standardized Residuals

The unusual observation table displays cases that meet one of two criteria:

Standardized residuals with absolutes values greater than 2. These cases do not follow the proposed regression equation well.
Leverages greater than the lesser of 3p/n or 0.99, where p is the number of terms in the model including the constant and n is the number of observations in the data set. These cases could have undue influence on the proposed regression equation.

For unusual observations, you should investigate whether the data were recorded correctly, and whether the data collection process was affected by any other factors.

Example Output

Fits and Diagnostics for Unusual Observations

Observed Std

Obs Probability Fit Resid Resid

50 1.000 0.062 2.357 2.40 R

68 1.000 0.091 2.189 2.28 R

R Large residual

Interpretation

For the cereal data, two observations, 50 and 68, have standardized residuals with absolute values greater than 2 (2.40 and 2.28). These two observations do not follow the proposed regression equation well.

Note	Residual plots can also help you examine the assumptions about the regression model.