Joint Factor Tests

In the Fit Least Squares report, the Joint Factor Test option appears when interaction effects are present. For each main effect in the model, JMP produces a joint test of whether all the coefficients for terms involving that main effect are zero. This test is conditional on all other effects being in the model. Specifically, the joint test is a general linear hypothesis test of a restricted model. In that model, all parameters that correspond to the specified effect and the interactions that contain it are set to zero.

Figure 3.24 Joint Factor Tests Report 

Note that the test for age has 15 degrees of freedom. This test involves five parameters for age, five parameters for age*sex, and five parameters for height*age. The null hypothesis for this test is that all 15 parameters are zero.