Model Fitting: Generalized Linear Models |
The Plots Tab
You can use the Plots tab (Figure 24.23)
to create plots that graphically display
results of the analysis. There are plots that help you to visualize
the fit, the residuals, and various influence diagnostics.
Creating a plot often adds one or more variables to the data table.
For a multinomial response, residuals and influence diagnostics are
not available, so the only possible plot for multinomial data is
the predicted response plot.
The following plots are available:
- Observed vs. Predicted
-
creates a scatter plot of the Y variables versus the predicted values,
overlaid with the diagonal line that represents a perfect fit.
- Predicted response plot
-
creates a line plot of the predicted probability versus the continuous
explanatory variable. This plot is created only if the following
conditions are satisfied:
- There is exactly one continuous explanatory variable.
- There are three or fewer classification
variables.
- There are 12 or fewer joint levels of the classification variables.
If the response distribution is multinomial, there are
plots, where is the number of response levels.
- Pearson chi-square residuals vs. Predicted
-
creates a scatter plot of the residuals versus the predicted probabilities.
- Deviance residuals vs. Predicted
-
creates a scatter plot of the deviance residuals versus the predicted
probabilities.
- Likelihood residuals vs. Predicted
-
creates a scatter plot of the likelihood residuals versus the
predicted probabilities.
- Cook's D vs. Observation number
-
creates a scatter plot of Cook's statistic for each observation.
- Leverage (H) vs. Observation number
-
creates a scatter plot of the leverage statistic for each observation.
Figure 24.23: The Plots Tab
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