Response Options
In the Fit Least Squares report, the red triangle menu options for the response contain options to customize the model report.
Regression Reports
Provides basic reports and report options. See Regression Reports.
Summary of Fit
Shows or hides a report that contains a summary of model fit statistics. See Summary of Fit.
Analysis of Variance
Shows or hides a report that contains statistics for comparing the fitted model to a simple mean model. See Analysis of Variance.
Parameter Estimates
Shows or hides a report that contains the parameter estimates and t tests for the hypothesis that each parameter is zero. See Parameter Estimates.
Effect Tests
Shows or hides a report that contains tests for the fixed effects in the model. See Effect Tests.
Effect Details
Shows or hides a report that contains details, plots, and tests for individual effects. See Effect Details.
When the Effect Leverage Emphasis option is selected, each effect has its own report at the top of the Fit Least Squares report window. This report includes effect details options as well as a leverage plot. See Effect Leverage Plots.
Lack of Fit
Shows or hides a test that assesses if the model has the appropriate effects, when that test can be conducted. See Lack of Fit.
Show All Confidence Intervals
Shows or hides confidence intervals for parameter estimates and least squares means estimates.
AICc
Shows or hides the corrected Akaike's Information Criterion (AICc) and the Bayesian Information Criterion (BIC) values in the Summary of Fit report. See “Likelihood, AICc, and BIC”.
Estimates
Provides options for further analyses relating to parameter estimates. See Estimates.
Show Prediction Expression
Shows or hides the Prediction Expression report, which contains the equation for the estimated model. See Show Prediction Expression.
Sorted Estimates
Shows or hides the Sorted Parameter Estimates report, which can be useful in screening situations. If the design is not saturated, this report is equivalent to the Parameter Estimates report with the terms, other than the Intercept, sorted in decreasing order of significance. If the design is saturated, then Pseudo t tests are provided. See Sorted Estimates.
Expanded Estimates
(Available only when at least one of the effects is not continuous.) Shows or hides the parameter estimates for all levels of a nominal model effect. For a nominal effect with k levels, the Parameter Estimates report contains coefficients for the k–1 parameters, and the Expanded Estimates table contains the effect coefficients for all k levels. See Expanded Estimates.
Indicator Parameterization Estimates
(Available only when there are nominal columns and an intercept among the model effects.) Shows or hides the Indicator Function Parameterization report, which contains parameter estimates with the nominal effects in the model parametrized using the classical indicator functions. See Indicator Parameterization Estimates.
Sequential Tests
Shows or hides the Sequential (Type 1) Tests report, which contains the sums of squares as effects are added to the model sequentially. This report contains F tests that are based on the sequential sums of squares. See Sequential Tests.
Custom Test
Enables you to test a custom hypothesis using a customized F test that contrasts the different effects in the model. See Custom Test.
Compare Slopes
(Available only when there is one nominal effect, one continuous effect, and their interaction effect for the fixed effects.) Generates an analysis of means (ANOM) report that compares interaction slopes with the average slope for an analysis of covariance (ANCOVA) model. See Compare Slopes.
Joint Factor Tests
(Available only when the model contains interactions.) Shows or hides a joint test for each main effect in the model. The joint test is for all of the parameters that involve that main effect. See Joint Factor Tests.
Inverse Prediction
Enables you to predict values of explanatory variables for one or more values of the response. See Inverse Prediction.
Cox Mixtures
(Available only when the model contains mixture effects.) Shows or hides parameter estimates for the Cox mixture model based on the specified reference mixture values. You can use these estimates to derive factor effects and estimate the response surface shape relative to a reference point in the design space. See Cox Mixtures.
Parameter Power
Adds or removes columns to the Parameter Estimates report. These columns contain power and other details that relate to the corresponding hypothesis tests. See Parameter Power.
Correlation of Estimates
Shows or hides the matrix of correlations between the parameter estimates for the specified fit. See Correlation of Estimates.
Error Specification
(Available only when the model contains no random effects.) Specifies the error variance and the error degrees of freedom that are used for standard errors and tests in the Fit Least Squares report. Note that the Studentized Residuals plot and the Box-Cox Transformations report are not affected by changing the Error Specification. When the Error Specification is Pure Error or Specified, an additional column appears in the Analysis of Variance report. See Analysis of Variance.
Default Estimate
Uses the standard root mean square error and error degrees of freedom from the model to calculate all tests and standard errors.
Pure Error
Uses the Pure Error mean square and associated degrees of freedom from the Lack of Fit report to calculate all tests and standard errors. See Lack of Fit.
Caution: If the pure error degrees of freedom is 1, a warning message is displayed indicating that tests are weak and confidence limits are large.
Specified
Uses user-specified values for the error variance and error degrees of freedom to calculate all tests and standard errors.
Effect Screening
Provides reports and plots for identifying significant effects. See Effect Screening.
Scaled Estimates
Shows or hides parameter estimates that correspond to factors that are scaled to have a mean of zero and a range of two. See Scaled Estimates and the Coding of Continuous Terms.
Normal Plot
Shows or hides a plot that identifies parameter estimates that deviate from normality. This can help you determine which effects are active. See Normal Plot Report.
Bayes Plot
Shows or hides a plot that computes posterior probabilities for all model terms using a Bayesian approach. See Bayes Plot Report.
Pareto Plot
Shows or hides a plot of the absolute values of the orthogonalized and standardized parameter estimates. This plot shows their composition relative to the sum of the absolute values. See Pareto Plot Report.
Factor Profiling
Provides profilers, interaction, and cube plots to examine how the response is related to the model terms. Also provides a plot and report for fitting a Box-Cox transformation. See Factor Profiling.
Note: If your model contains an expression or vector as an effect, most of these options are not available.
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 enables you to find optimum settings for one or more responses and to explore response distributions using simulation. See Profiler and “Profiler” in Profilers.
Interaction Plots
(Available only when the model contains interaction effects.) Shows or hides a matrix of interaction plots. See Interaction Plots.
Contour Profiler
(Available only when the model contains more than one continuous factor.) Shows or hides the contour profiler, which shows the contours of the response graphically for two factors at a time. See Contour Profiler and “Contour Profiler” in Profilers.
Mixture Profiler
Shows or hides a mixture profiler that shows the contours of the response on a ternary plot. See Mixture Profiler and “Mixture Profiler” in Profilers.
Note: This option is available only if the Mixture Effect attribute is applied to three or more factors in the model or the Mixture column property is applied to three or more factor columns.
Cube Plots
Shows or hides the predicted values for the extremes of the factor ranges laid out on the vertices of cubes. See Cube Plots.
Box Cox Y Transformation
Shows or hides the Box-Cox Transformations report, which shows how the fit would change if you refit the model with a power (Box-Cox) transformation on the response. See Box-Cox Y Transformation.
Surface Profiler
Shows or hides a three-dimensional surface plot of the response surface. See Surface Profiler and “Surface Plot” in Profilers.
Row Diagnostics
Provides plots and reports for examining residuals. Also reports the PRESS statistic and provides a Durbin-Watson test. See Row Diagnostics.
Plot Regression
Shows or hides the Regression Plot report, which contains a scatterplot of the data and regression lines for each level of the categorical effect.
Note: This option is available only if there is exactly one continuous effect and no more than one categorical effect in the model. If these conditions are met, the Regression Plot report is provided by default.
Plot Actual by Predicted
Shows or hides the Actual by Predicted plot, which plots the observed values of the response against the predicted values of the response. This plot is the leverage plot for the whole model. See Effect Leverage Plots.
Note: The Actual by Predicted Plot is shown by default when Effect Leverage or Effect Screening is selected as the Emphasis in the Fit Model launch window and the RSquare value is less than 0.999.
Plot Effect Leverage
Shows or hides the Leverage Plot report for each effect in the model. The plot shows how observations influence the test for that effect and gives insight about multicollinearity. See Effect Leverage Plots.
Note: Effect Leverage Plots are shown by default when Effect Leverage is selected as the Emphasis in the Fit Model launch window and the RSquare value is less than 0.999. They appear to the right of the Whole Model report. When another Emphasis is selected, the Effect Leverage Plots appear in the Effect Details report. In all cases, the option Regression Reports > Effect Details must be selected in order for Effect Leverage plots to display.
Plot Residual by Predicted
(Available only for continuous responses.) Shows or hides a plot with the residuals on the vertical axis and the predicted values of the response on the horizontal axis. You typically want to see the residual values scattered randomly about zero.
Note: The Residual by Predicted Plot is shown by default when Effect Leverage or Effect Screening is selected as the Emphasis in the Fit Model launch window and the RSquare value is less than 0.999.
Plot Residual by Row
Shows or hides a plot with the residual values on the vertical axis and the row numbers on the horizontal axis. This plot can help you detect patterns that result from the row ordering of the observations.
Plot Studentized Residuals
Shows or hides the Studentized Residuals plot, which plots the studentized residuals on the vertical axis and the row number on the horizontal axis. Each point on the plot is computed using an estimate of its standard deviation obtained with the current observation deleted. These residuals are also called RStudent or externally Studentized residuals.
The plot contains two sets of limits:
• The outer limits that appear in red on the plot are 95% Bonferroni limits. These limits are placed at ± tQuantile(0.025/n, n–p–1), where n is the number of observations and p is the number of parameters (including the intercept).
• The inner limits that appear in green on the plot are 95% individual t distribution limits. These limits are placed at ± tQuantile(0.025, n–p–1), where n is the number of observations and p is the number of parameters (including the intercept).
Points that fall outside the red limits should be treated as probable outliers. Points that fall outside the green limits but within the red limits should be treated as possible outliers, but with less certainty. You can change the confidence level of 95% for these limits by selecting the Set Alpha Level option in the Model Specification window.
Caution: The residuals that are saved using Save Columns > Studentized Residuals are not externally Studentized.
Note: If the model contains random effects and REML is the specified Method in the launch window, the Studentized Residuals plot does not contain limits and the points that are plotted are not externally Studentized.
Plot Residual by Normal Quantiles
(Not available when REML is the specified Method in the launch window.) Shows or hides a plot with the residual values on the vertical axis and the normal quantiles of the residuals on the horizontal axis. This plot can help you assess the assumption of normality of the residuals.
Press
Shows or hides the Press Report, which contains the Press statistic and its root mean square error (RMSE). The Press statistic is useful when comparing multiple models. Models with lower Press statistics are favored. See Press.
Durbin-Watson Test
(Not available when you specify a Frequency column.) Shows or hides the Durbin-Watson report, which contains a statistic to test whether the residuals have first-order autocorrelation. The report also shows the autocorrelation of the residuals and the exact probability associated with the statistic. This option is appropriate only for time series data and assumes that your observations are in time order.
Save Columns
Saves model results as columns in the data table, except for Save Coding Table, which saves results in a separate data table. See Save Columns.
Prediction Formula
Saves a new formula column to the data table. The new column contains the prediction formula for the fitted model. The column includes both a Notes and a Predicting column property that note the source of the prediction.
Note: The saved prediction formula column inherits certain properties from the response column. These properties include Response Limits, Spec Limits, and Control Limits. If you change these properties for the response column after selecting this option, the properties in the saved prediction formula column will not be updated.
See Prediction Formula.
Caution: The predicted values saved by the Prediction Formula option are not valid when a Weight variable has been specified in the analysis.
Prediction and Interval Formulas
Saves new formula columns to the data table. The columns contain formulas for the predictions, confidence limits, and prediction limits. All columns are hidden by default except for the prediction formula column.
Tip: The limits columns that are created by this option contain properties that are used by the Prediction Profiler. Select this option if you want to use these limits in the profiler.
Note: If you press Shift while selecting the option, you are prompted to enter an α level for the computations.
Predicted Values
Saves a new column to the data table. The new column contains the predicted values for the fitted model. The column includes both a Notes and a Predicting column property that note the source of the prediction.
Note: The saved column inherits certain properties from the response columns. These properties include Response Limits, Spec Limits, and Control Limits. If you change these properties for the response column after selecting this option, the properties in the saved column will not be updated.
Residuals
Saves a new column to the data table. The new column contains the observed response values minus their predicted values for the fitted model.
Mean Confidence Interval
Saves two new columns to the data table. The new columns contain the lower and upper 95% confidence limits for the mean response. This encompasses the variation in the estimation, but not in the response.
Note: If you press Shift while selecting the option, you are prompted to enter an α level for the computations.
Indiv Confidence Interval
Saves two new columns to the data table. The new columns contain lower and upper 95% confidence limits for individual response values. This encompasses the variation in both the response and its estimation.
Note: If you press Shift while selecting the option, you are prompted to enter an α level for the computations.
Studentized Residuals
Saves a new column to the data table. The new column contains the studentized residuals, which are the residuals divided by their standard errors.
Externally Studentized Residuals
(Not available when the fitting method is REML.) Saves a new column to the data table. The new column contains the residuals divided by standard error estimates that exclude the current row. See Plot Studentized Residuals.
Hats
Saves a new column to the data table. The new column contains the diagonal values of the matrix X(X′X)−1X′. These values are sometimes called hat or leverage values.
Std Error of Predicted
Saves a new column to the data table. The new column contains the standard error for predicted values. This is used to compute the mean confidence interval.
Std Error of Residual
Saves a new column to the data table. The new column contains the standard error for residual values. This is used to compute the studentized residuals.
Std Error of Individual
Saves a new column to the data table. The new column contains the standard error of an individual predicted response value. This is used to compute the individual confidence interval.
Effect Leverage Pairs
Saves a set of new columns to the data table. The new columns contain the X Leverage values and Y Leverage Residuals for each leverage plot. For each effect in the model, two columns are added. If the response column name is R and the effect is X, the new column names are:
– X Leverage of X for R
– Y Leverage of X for R
In the columns panel, these columns are organized in a columns group called Leverage. The Y value is the partial residual. The X value is the regressor shrinkage in the effect leverage plots.
Cook’s D Influence
Saves a new column to the data table. The new column contains values of the Cook’s D influence statistic, which is a measure of how much influence each observation has in estimating the model.
StdErr Pred Formula
Saves a new formula column to the data table. The new column contains the formula for the standard error of the predicted values as a function of the regressors.
Tip: The saved formula can be large. If you do not need the formula, use the Std Error of Predicted option.
Mean Confidence Limit Formula
Saves two new formula columns to the data table. The columns contain the formulas for lower and upper 95% confidence limits for the mean response as a function of the regressors.
Note: If you press Shift while selecting the option, you are prompted to enter an α level for the computations.
Indiv Confidence Limit Formula
Saves two new formula columns to the data table. The columns contain the formulas for lower and upper 95% confidence limits for an individual response value as a function of the regressors.
Note: If you press Shift while selecting the option, you are prompted to enter an α level for the computations.
Save Coding Table
Creates a new data table that contains the JMP coding for all model parameters. The last column gives the values of the response variable. If you entered more than one response column, all of these columns appear as the last columns in the coding table.
Note: The coding data table contains a table variable called Original Data that contains the name of the data table that was used for the analysis. In the case where a By variable is specified, the Original Data table variable contains the By variable and its level.
Publish Prediction Formula
Creates a prediction formula and publishes it as a formula column script in the Formula Depot platform. If a Formula Depot report is not open, this option creates a Formula Depot report. See “Formula Depot” in Predictive and Specialized Modeling.
Publish Standard Error Formula
Creates a standard error formula and publishes it as a formula column script in the Formula Depot platform. If a Formula Depot report is not open, this option creates a Formula Depot report. See “Formula Depot” in Predictive and Specialized Modeling.
Publish Mean Confid Limit Formula
Creates confidence limit formulas for the mean response and publishes them as formula column scripts in the Formula Depot platform. If a Formula Depot report is not open, this option creates a Formula Depot report. See “Formula Depot” in Predictive and Specialized Modeling.
Publish Indiv Confid Formula
Creates confidence limit formulas for an individual response and publishes them as formula column scripts in the Formula Depot platform. If a Formula Depot report is not open, this option creates a Formula Depot report. See “Formula Depot” in Predictive and Specialized Modeling.
Multiple Comparisons
Enables you to specify comparisons among effect levels. These comparisons can involve a single effect or you can define flexible custom comparisons. You can compare to the overall mean, to a control mean, or you can obtain all pairwise comparisons using Tukey HSD or Student’s t. When you specify the Student’s t method, you can also perform equivalence tests to identify pairwise differences that are of practical importance. See Multiple Comparisons.
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 from 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.
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.