Modeling and Multivariate Methods - SAS

Chapter 2 Introduction to the Fit Model Platform 51
Model Specification Options
Table 2.7 Descriptions of the Model Specification Options (Continued)
Create SAS job
Submit to SAS
Load Version 3 Model
Convergence Settings
Creates a SAS program in a script window that can recreate the current
analysis in SAS. Once created, you have several options for submitting the
code to SAS.
1. Copy and paste the resulting code into the SAS Program Editor. This
method is useful if you are running an older version of SAS (pre-version
8.2).
2. Select Edit > Submit to SAS.
3. Save the file and double-click it to open it in a local copy of SAS. This
method is useful if you would like to take advantage of SAS ODS
options, such as generating HTML or PDF output from the SAS code.
See the Using JMP book.
Submits code to SAS and displays the results in JMP. If you are not
connected to a SAS server, prompts guide you through the connection
process.
See the Using JMP book.
Opens a text file that contains JMP version 3 model statements into the Fit
Model platform. You can save the model as the current version.
Note: This option appears only if your model includes a random effect.
If your model includes a Random Effect, or if you select Generalized
Linear Model as the personality, and REML is selected as the method in the
launch window, a new menu called Convergence Settings appears in the
red triangle menu next to Model Specification. The Convergence Settings
menu includes the following options:
• Maximum Iterations
• Convergence Limit
Default values for the Maximum Iterations and Convergence Limit are 100
and .00000001, respectively. When you click on either of these options, you
are able to enter new values for these limits. If you have a very large data set
or a complicated model, you might want to limit the number of iterations. If
your model does not readily converge, you might want to either increase the
Maximum Iterations or increase the Convergence Limit.
Note: JMP only creates design columns for those combinations that
actually occur in the data.