Binary Fitted Line Plot

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

Obs Probability Fit Resid Std Resid

32 0.0000 0.0637 -0.3627 -0.39 X

58 1.0000 0.1486 1.9526 2.02 R

R Large residual

X Unusual X

Interpretation

For the health care center data, two observations, 32 and 58, are unusual. Observation 32 has a large leverage value. Observation 58 has a standardized residual with absolute value greater than 2 (2.02). Observation 58 does not follow the proposed regression equation well. You can fit the model with and without these observations to explore how much influence the observations have on the results.

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