Generalized Linear Model Fit Report Options
The Generalized Linear Model Fit red triangle menu contains the following options:
Custom Test
Enables you to test a custom hypothesis. For more information about custom tests, see “Custom Test”.
Contrast
Runs a customized F test for the statistical contrasts of treatment levels that you specify in the contrasts dialog. If a contrast involves a covariate, you can specify the value of the covariate at which to test the contrast. For an example of the Contrast option, see Example of Using Contrasts in a Generalized Linear Model.
Note: The Contrast option for a generalized linear model is similar to the corresponding option for a regression model with a single response. See “LSMeans Contrast” for a description and examples of the LSMeans Contrast options.
Inverse Prediction
(Available only for continuous effects.) Generates a predicted X value and confidence interval based on specific values of Y and all other factors. For more information about the Inverse Prediction option, see “Inverse Prediction”.
Covariance of Estimates
Shows or hides a covariance matrix for all the effects in a model. The estimated covariance matrix of the parameter estimator is defined as follows:
Σ = -H-1
where H is the Hessian (or second derivative) matrix evaluated using the parameter estimates on the last iteration. Note that the dispersion parameter, whether estimated or specified, is incorporated into H. Rows and columns corresponding to aliased parameters are not included in Σ.
Correlation of Estimates
Shows or hides a correlation matrix for all the effects in a model. The correlation matrix is the normalized covariance matrix. For each σij element of Σ, the corresponding element of the correlation matrix is σij/σiσj, where 
.
Profilers
Provides various profilers that enable you to explore the fitted model.
Profiler
Shows or hides the Prediction Profiler, which is used to graphically explore the prediction equation by slicing it one factor at a time. The prediction profiler contains features for optimization. For more information about the prediction profiler, see “Profiler” in Profilers.
Contour Profiler
Shows or hides the contour profiler, which shows the contours of the response graphically for two factors at a time. For more information about the contour profiler, see “Contour Profiler” in Profilers.
Surface Profiler
Shows or hides an interactive surface plot for the response. For more information about the surface profiler, see “Surface Plot” in Profilers.
Diagnostic Plots
Provides various plots to help assess how well the current model fits. These plots enable you to search for outliers and determine the adequacy of your model. For more information about deviance, see Statistical Details for Model Selection and Deviance. The following plots are available:
Studentized Deviance Residuals by Predicted
Shows or hides a plot of studentized deviance residuals on the vertical axis and the predicted response values on the horizontal axis.
Studentized Pearson Residuals by Predicted
Shows or hides a plot of the studentized Pearson residuals on the vertical axis and the predicted response values on the horizontal axis.
Deviance Residuals by Predicted
Shows or hides a plot of the deviance residuals on the vertical axis and the predicted response values on the horizontal axis.
Pearson Residuals by Predicted
Shows or hides a plot of the Pearson residuals on the vertical axis and the predicted response values on the horizontal axis.
Regression Plot
(Available only when there is one continuous predictor and no more than one categorical predictor.) Shows or hides a plot of the response on the vertical axis and the continuous predictor on the horizontal axis. A regression line is shown over the points. If there is a categorical predictor in the model, each level of the categorical predictor has a separate regression line and a legend appears next to the plot.
Linear Predictor Plot
(Available only when there is one continuous predictor and no more than one categorical predictor.) Shows or hides a plot of responses transformed by the inverse link function on the vertical axis and the continuous predictor on the horizontal axis. A transformed regression line is shown over the points. If there is a categorical predictor in the model, each level of the categorical predictor has a separate transformed regression line and a legend appears next to the plot.
Save Columns
Shows a submenu of options that enable you to save certain quantities as new columns in the current data table. For more information about the residual formulas, see Residual Formulas.
Prediction Formula
Saves a new formula column to the data table. The new column contains a formula for the predicted values for the mean, as computed by the specified model.
Predicted Values
Saves a new column to the data table. The new column contains the values predicted by the model.
Mean Confidence Interval
Saves new columns to the data table. The new columns contain the 95% confidence limits for the prediction equation for the model. These confidence limits reflect the variation in the parameter estimates.
Note: You can change the α level for the confidence limits in the Fit Model window by selecting Set Alpha Level from the Model Specification red triangle menu.
Save Indiv Confid Limits
Saves new columns to the data table. The new columns contain the 95% confidence limits for a given individual value for the model. These confidence limits reflect variation in the error and variation in the parameter estimates.
Note: You can change the α level for the confidence limits in the Fit Model window by selecting Set Alpha Level from the Model Specification red triangle menu.
Deviance Residuals
Saves a new column to the data table. The new column contains the deviance residuals.
Pearson Residuals
Saves a new column to the data table. The new column contains the Pearson residuals.
Studentized Deviance Residuals
Saves a new column to the data table. The new column contains the studentized deviance residuals.
Studentized Pearson Residuals
Saves a new column to the data table. The new column contains the studentized Pearson residuals.
Model Dialog
Shows the completed Fit Model launch window for the current analysis.
Effect Summary
Shows or hides the Effect Summary report, which enables you to interactively update the effects in the model. See “Effect Summary Report”.
See “Local Data Filters in JMP Reports”, “Redo Menus in JMP Reports”, “Group Platform”, and “Save Script Menus in JMP 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.
Platform Preferences
Contains options that enable you to view the current platform preferences or update the platform preferences to match the settings in the current JMP report.
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.
Note: Additional options for this platform are available through scripting. Open the Scripting Index under the Help menu. In the Scripting Index, you can also find examples for scripting the options that are described in this section.