Parameter Estimates for Generalized Linear Models
The Parameter Estimates table for generalized
linear models, as illustrated by Figure 39.18, includes the following:
- names the variable associated with the estimated parameter.
The name INTERCEPT represents the estimate of the intercept
- is the degrees of freedom associated
with each parameter estimate.
There is one degree of freedom
unless the model is not full rank.
In this case, any parameter that is confounded with previous
parameters in the model has its degrees of freedom set to 0.
- is the parameter estimate.
- Std Error
- is the estimated standard deviation of the parameter estimate.
- is the test statistic
for testing that the parameter is 0.
This is computed as the square of the ratio of the
parameter estimate divided by the standard error.
- Pr > ChiSq
- is the probability of obtaining an statistic greater than that observed given that
the true parameter is 0.
A small p-value is evidence for
concluding that the parameter is not 0.
Figure 39.18: Parameter Estimates Table for Generalized Linear Models
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.