The Fit Mixed ReportProduces reports that relate to the mixed model fit. These reports give estimates and tests for model parameters, as well as fit statistics. See Model Reports.
Opens the Multiple Comparisons dialog window where you can select one or more effects and initial comparisons. This report is available for categorical fixed effects. See Multiple Comparisons.
(Available only when there is one nominal term, one continuous term, and their interaction effect for the fixed effects.) Produces a report that enables you to compare the slopes of each level of the interaction effect in an analysis of covariance (ANCOVA) model. See Compare Slopes.
For one or more values of the response, predicts values of explanatory variables. See Inverse Prediction in Standard Least Squares Report and Options.
Produces plots based on marginal predicted values and marginal residuals. These plots display the variation due to random effects. See Marginal Model Inference.
Produces plots based on conditional predicted values and conditional residuals. These plots display the variation that remains, once random effects are accounted for. See Conditional Model Inference.
See Local Data Filter, Redo Menus, and Save Script Menus in the Using JMP book for more information about the following options:
Shows report of random effects covariance parameter estimates. This report appears when you specify random effects in the launch window. See Random Effects Covariance Parameter Estimates.
Shows report of repeated effects covariance parameter estimates. This report appears when you specify repeated effects in the launch window. See Repeated Effects Covariance Parameter Estimates.
(Available only when there are nominal columns among the fixed effects.) Displays the Indicator Function Parameterization report. This report gives parameter estimates for the fixed effects based on a model where nominal fixed effect columns are coded using indicator (SAS GLM) parameterization and are treated as continuous. Ordinal columns remain coded using the usual JMP coding scheme. The SAS GLM and JMP coding schemes are described in The Factor Models in Statistical Details.
Shows report of random coefficients. This report appears when you specify random effects in the launch window. See Random Coefficients.