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To fit models using the mixed model personality, select Analyze > Fit Model and then select Mixed Model from the Personality list. Note that when you enter a continuous variable in the Y list before selecting a Personality, the Personality defaults to Standard Least Squares.
The fixed effects for analysis of the Split Plot.jmp sample data table appear in Figure 8.7. Note that it is possible to have no fixed effects in the model. For an example, see Spatial Example: Uniformity Trial.
Figure 8.7 Fit Model Launch Window Showing Completed Fixed Effects
Figure 8.8 shows the random effects specification for the Split Plot.jmp sample data where Carcass is a random block. Split Plot Example describes the example in detail.
Figure 8.8 Fit Model Launch Window Showing Completed Random Effects Tab
2.
Select the Random Effects tab and then Add.
4.
Click the Nest Random Coefficients button.
Random coefficients are modeled using an unstructured covariance structure. Figure 8.9 shows the random coefficients specification for the Wheat.jmp sample data. (See also Example Using Mixed Model.)
Figure 8.9 Completed Fit Model Launch Window Showing Random Coefficients
Figure 8.10 Completed Fit Model Launch Window Showing Repeated Structure Tab
Table 8.1 lists the covariance structures available, the requirements for using each structure, and the number of covariance parameters for the given structure. The number of observation times is denoted by J.
J(J+1)/2
J+1
2J-1
2J-1

Help created on 3/19/2020