Example of Nominal Logistic Regression
Use the Logistic platform to examine the relationship between a nominal Y response variable and a continuous X factor variable. The data in this example come from an experiment where 5 groups, each containing 12 rabbits, were injected with streptococci bacteria. Once the rabbits were confirmed to have the bacteria in their system, they were given different doses of penicillin. You want to find out whether the natural log of dosage amounts has any effect on whether the rabbits are cured.
1. Select Help > Sample Data Folder and open Penicillin.jmp.
2. Select Analyze > Fit Y by X.
3. Select Response and click Y, Response.
4. Select ln(dose) and click X, Factor.
Notice that JMP automatically fills in Count for Freq, because the Count column was previously assigned the role of Freq.
5. From the Target Level list, select Cured.
6. Click OK.
Figure 8.2 Example of Nominal Logistic Report
The plot shows the fitted model as a function of ln(dose). The fitted model is the predicted probability of being cured. The p-value is significant, which indicates that the dosage amounts have a significant effect on whether the rabbits are cured. The marginal distribution that is shown on the right vertical axis represents the probabilities for the levels of the Y variable if there is no association between the X and Y variables.
Tip: To change the response level that is analyzed, use the Target Level option in the launch window or use the Value Order column property.