Example of the Response Screening Personality
This example uses the Response Screening personality in Fit Model to study tests of multiple responses against linear model effects.
1. Select Help > Sample Data Folder and open Drosophila Aging.jmp.
2. Select Analyze > Fit Model.
3. Select all the continuous columns and click Y.
4. Select channel and click Add.
5. Select line, sex, and age and select Macros > Full Factorial.
6. Select Response Screening from the Personality list.
7. Click Run.
8. Click the Fit Response Screening red triangle and select Save Effect Tests.
9. Run the FDR Logworth by Effect Size script in the Effect Tests data table.
10. Select Rows > Data Filter.
11. In the Data Filter window, select Effect and click 
.
12. In the Data Filter, click each of the model effects sequentially while you view the selected points in the FDR Logworth vs. Effect Size plot.
Figure 24.16 FDR Logworth vs. Rank Fraction Plot with line*age Tests Selected
Keep in mind that logworth values that exceed 2 are significant at the 0.01 level. The Data Filter helps you see that, with the exception of sex and channel, the model effects are rarely significant at the 0.01 level. The points for tests of the line*age interaction effect are selected. None of these are significant at the 0.01 level.