Simple Split Plot or Repeated Measures Model
Here A is the whole plot variable, B[A] is the whole plot ID, and C is the split plot, or repeated measures, variable.
Effects to be entered: A, B[A]&Random, C, C*A
1. In the Select Columns list, select two nominal or ordinal effects, A and B.
2. Click Add.
3. To nest B within A: In the Construct Model Effects list, select B. In the Select Columns list, select A. The two effects should be highlighted.
4. Click Nest.
5. In the Construct Model Effects list, select B[A].
6. Select Attributes > Random Effect.
7. In the Select Columns list, select a third nominal or ordinal effect, C.
8. Click Add.
9. In the Construct Model Effects list, select C. In the Select Columns list, click A. Both effects should be highlighted.
10. Click Cross.
Example of a Simple Repeated Measures Model
You have data on the distance traveled by each of six animals in each of the four seasons. There are two species and the animal identifier is nested within species. Since these six animals are representatives of larger species populations, you decide to treat subject as a random effect. You want to model the response, miles, as a function of species and season, accounting for the fact that there are repeated measures for each animal.
1. Select Help > Sample Data Library and open Animals.jmp.
2. Select Analyze > Fit Model.
3. In the Select Columns list, select miles and click Y.
4. In the Select Columns list, select species and subject.
5. Click Add.
6. To nest subject within species: In the Construct Model Effects list, select subject. In the Select Columns list, select species. The two effects should be highlighted.
7. Click Nest.
8. In the Construct Model Effects list, select subject[species].
9. Select Attributes > Random Effect.
10. In the Select Columns list, select season.
11. Click Add.
12. In the Construct Model Effects list, select season. In the Select Columns list, click species. Both effects should be highlighted.
13. Click Cross.
Figure 2.19 Fit Model Window for Simple Repeated Measures Model
