To create the two new
variables, complete the following steps:
-
-
Click the
in the upper right corner of the visualization and select
Derive Predicted Values.
-
-
Click
OK. The
predicted values for the logistic regression appear in the
Category variables
section. All other variables, including the predicted values for the
other models, appear in the
Prediction variables
section.
Depending on the chosen visualization, the information contained in each variable
is slightly different.
Predicted Values
For linear regressions and generalized linear models, this is a
numeric value that is the value generated by the regression model. Or, this is the value that would
have been generated by the regression model
if the observation was scored by the model.
For logistic regressions, this is the decision generated by the logistic regression
based on the calculated probability and
Prediction cutoff property. All
observations are classified into either the
event level of interest, not the event level of interest, or missing.
Residual Values
The computed residual for each observation. Available for the linear regression and
generalized linear model visualizations.
Probability Values
The computed probability for each observation. Observations with probability values
that are greater than or equal to the Prediction cutoff property are predicted to be in the event level of interest. Observations with probability
values that are less than the Prediction cutoff property
are considered to be not in the event level or interest. That is,
there is no prediction made regarding each individual measurement
level, only between the measurement level of interest and everything
else.