Modeling and Multivariate Methods - SAS

208 Performing Logistic Regression on Nominal and Ordinal Responses Chapter 7
Logistic Fit Platform Options
Two-level nominal effects are coded 1 and -1 for the first and second levels, so range odds ratios or their
reciprocals would be of interest.
Dose Response Example
In the Dose Response.jmp sample data table, the dose varies between 1 and 12.
1. Open the Dose Response.jmp sample data table.
2. Select Analyze > Fit Model.
3. Select response and click Y.
4. Select dose and click Add.
5. Click OK.
6. From the red triangle next to Nominal Logistic Fit, select Odds Ratio.
Figure 7.10 Odds Ratios
The unit odds ratio for dose is 1.606 (which is exp(0.474)) and indicates that the odds of getting a Y =0
rather than Y = 1 improves by a factor of 1.606 for each increase of one unit of dose. The range odds ratio
for dose is 183.8 (exp((12-1)*0.474)) and indicates that the odds improve by a factor of 183.8 as dose is
varied between 1 and 12.
Inverse Prediction
For a two-level response, the Inverse Prediction command finds the x value that results in a specified
probability.
To see an example of inverse prediction:
1. Open the Ingots.jmp sample data table.
2. Select Analyze > Fit Y by X.
3. Select ready and click Y, Response.
4. Select heat and click X, Factor.
5. Select count and click Freq.