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OCR: Model Fitting: Random Effects JMP supports mixea models with random effects to a degree For example in balancec repeated measures and split plots, this means that the test for some of the effects wil done respect to another effect used for the denominator, rather than the residual me square some cases, linear com bination of mean squares needed to synthesize denominator that has the same expectation as the numerator under the null hypothe To specify an effect as Random highlight it in the Model dialog. and chooRandom Effect from the Effect Attributes menu The effect will have theRandom }label appended to it When the model ic and the sums of squares and mean squares for eac effect are calcula ted, JMP will obtain an expression for the expected value of each mean square in terms of the varia ...