The Fit Mixed Report
The Fit Mixed red triangle menu contains the following options:
Model Reports
Produces 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.
Linear Combination of Variance Components
Shows a report that enables you to compute confidence intervals for linear combinations of variance components. Initially, the report contains an editable text box and a table of variance components in the model. Use the text box to label the linear combination. Enter values in the cells in the right column of the table to specify the linear functions for your confidence intervals. After you specify a linear combination of parameters and click Done, a table appears that contains confidence intervals for the specified linear combination.
The table contains an estimate and standard error, as well as two types of confidence intervals (Satterthwaite and Wald) and a Wald p-value. The Wald p-value corresponds to a hypothesis test that the estimate differs from zero.
Tip: The Satterthwaite confidence interval is restricted to positive values, so it is not recommended for cases where the specified coefficients are negative. If the estimate is negative, the Satterthwaite confidence interval cannot be constructed and is reported as missing.
Multiple Comparisons
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.
Compare Slopes
(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.
Inverse Prediction
For one or more values of the response, predicts values of explanatory variables. See Inverse Prediction.
Marginal Model Inference
Produces plots based on marginal predicted values and marginal residuals. These plots display the variation due to random effects. See Marginal Model Inference.
Conditional 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.
Save Columns
Contains options to save various model results as columns in the data table. See Save Columns.
Model Dialog
Opens the completed Fit Model launch window for the current analysis. See Fit Model Launch Window.
See Local Data Filters in Reports, Redo Menus in Reports, and Save Script Menus in Reports in Using JMP for more information about the following options:
Local Data Filter
Shows or hides the local data filter that enables you to filter the data used in a specific report.
Redo
Contains options that enable you to repeat or relaunch the analysis. In platforms that support the feature, the Automatic Recalc option immediately reflects the changes that you make to the data table in the corresponding report window.
Save Script
Contains options that enable you to save a script that reproduces the report to several destinations.
Save By-Group Script
Contains options that enable you to save a script that reproduces the platform report for all levels of a By variable to several destinations. Available only when a By variable is specified in the launch window.
Model Reports
The reports available under Model Reports are determined by the type of analysis that you conduct. Several of these reports are shown by default.
Fit Statistics
Shows report for model fit statistics. See Fit Statistics.
Random Effects Covariance Parameter Estimates
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.
Fixed Effects Parameter Estimates
Shows report of fixed effects parameter estimates. See Fixed Effects Parameter Estimates.
Repeated 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.
Indicator Parameterization 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.
Caution: Standard errors, t-ratios, and other results given in the Indicator Function Parameterization report differ from those in the Parameter Estimates report. This is because the estimates are estimating different parameters.
Random Coefficients
Shows report of random coefficients. This report appears when you specify random effects in the launch window. See Random Coefficients.
Random Effects Predictions
Shows report of random effect predictions. This report appears when you specify random effects in the launch window. See Random Effects Predictions.
Fixed Effects Test
(Available only for models that contain at least one fixed effect.) Shows tests of fixed effects. This report appears when you specify fixed effects in the launch window. See Fixed Effects Tests.
Sequential Tests
(Available only for models that contain at least one fixed effect.) Shows the Sequential (Type 1) Tests report that contains the sums of squares as effects are added to the model sequentially. Conducts F tests based on the sequential sums of squares. See Sequential Tests.