Fit Response Screening Options
The Fit Response Screening red triangle menu contains options to save the calculated data.
Effect Tests
(Available only if fixed effects are specified in the launch window.) Shows or hides the Effect Tests table. See Effect Tests Table.
Effect Plots
(Available only if fixed effects are specified in the launch window.) Shows or hides the FDR PValue Plot for Effects and the FDR Logworth by Effect Size plot.
Overall Report
(Available only if no random effects are specified in the launch window.) Shows or hides the Overall Fit table, which contains a row for each Y variable. For each Y, the columns in the table summarize information about the model fit. If you select the Robust Fit option on the launch window, the models are fit using Huber M-estimation. The table contains the following columns:
Y
The specified response columns.
RSquare
The multiple correlation coefficient.
RMSE
The Root Mean Square Error.
Count
The number of observations (or sum of the Weight variable).
Overall FRatio
The test statistic for model fit from the Analysis of Variance report in Least Squares Fit.
Overall PValue
The p-value for the overall test of model significance.
Overall Logworth
The logworth of the p-value for the overall test of model significance.
Overall FDR PValue
The overall p-value adjusted for the false discovery rate. (See The Response Screening Report.)
Overall FDR Logworth
The logworth of the Overall FDR PValue.
Overall Rank Fraction
(Not shown by default.) The rank of the Overall FDR Logworth expressed as a fraction of the number of tests. If the number of tests is m, the largest Overall FDR Logworth value has Rank Fraction 1/m, and the smallest has Rank Fraction 1.
Overall Plots
(Available only if no random effects are specified in the launch window.) Shows or hides the Overall FDR PValue Plot and the FDR Logworth by RSquare plot.
Least Squares Means
Shows or hides a table that contains least squares means, standard errors, and confidence intervals. Each row in the table corresponds to a response and a combination of categorical effect settings. The least squares mean, standard error, and confidence interval is calculated for each combination of settings. Least squares means, or marginal means, are values predicted by the model for the levels of a categorical effect where the other model factors are set to neutral values. The neutral value for a continuous effect is defined to be its sample mean.
Sliced LSMeans Differences
Shows or hides an LSMeans Differences table and an FDR Logworth By LSMeans Difference plot. The LSMeans Differences table contains tests comparing all least square means on main effects and slices of two factor and three factor interactions. There are selection tables next to the plot that enable you select specific combinations effects and responses and view the selections on the plot.
A sliced comparison compares interactions by varying only one of the terms in the interaction. For example, when comparing levels of a Sex*Age interaction, comparing Sex=M and Age=12 to Sex=F and Age=16 is not as relevant as the sliced comparisons. Two sliced comparisons would be, Sex=M and Age=12 versus Sex=F and Age=12, and Sex=M and Age=12 versus Sex=M and Age = 15. In each instance, only one factor changes.
Select Effects Where
Opens the Select Where window. You can select specific responses in the Effects Tests table that correspond to a particular condition by using the Comparison menu and Value text box. For example, you can select all effects such that Effect Size > 0.80. After you click OK, the responses are selected in the Result Table.
Tip: You can also access the Select Where window by right-clicking anywhere in the Effect Tests table.
Select Responses for Selected Effects
Selects response columns in the original data table that correspond to the selected effects in the Effect Tests table.
Save Effect Tests
(Available only if fixed effects are specified in the launch window.) Creates a new data table that contains a row for each effect test. The Effect Tests data table contains a table variable called Original Data that gives the name of the data table that was used for the analysis. If you specified a By variable the Original Data variable also gives the By variable and its level.
Save Overall Fit
(Available only if no random effects are specified in the launch window.) Creates a new data table that contains one row per response variable. The Overall Fit data table contains a table variable called Original Data that gives the name of the data table that was used for the analysis. If you specified a By variable the Original Data variable also gives the By variable and its level.
Save Estimates
Creates a new data table that contains a row for each response variable and a column for each model term. The entries are the parameter estimates obtained by fitting the specified model. This data table also contains a table variable called Original Data that gives the name of the data table that was used for the analysis. If you specified a By variable, JMP creates an estimates table for each level of the By variable, and the Original Data variable gives the By variable and its level.
Save Least Squares Means
Creates a new data table in which each row corresponds to a response and a combination of effect settings. The row contains the least squares mean, standard error, and confidence interval for that combination of settings.
Save LSMeans Differences
Creates a new data table that contains the sliced least squares means differences, as well as their standard errors and confidence intervals. This data table also contains tests that compare all least square means for main effects and slices of two factor and three factor interactions.
Save BLUPS
(Available only if random effects are specified in the launch window.)Creates a new data table that contains the best linear unbiased predictors (BLUPs) for the random effects in the model.
Save Prediction Formula
Saves a new formula column for each response to the data table. Each column contains a prediction equation for the corresponding response.
Save Predicted Values
Saves a new column for each response to the data table. Each column contains the predicted values for the corresponding response.
Save Conditional Prediction Formula
(Available only if random effects are specified in the launch window.) Saves a new formula column for each response to the data table. Each column contains the conditional prediction formula for the corresponding response. The formula includes the random effects estimates.
Save Conditional Predicted Values
(Available only if random effects are specified in the launch window.) Saves a new column for each response to the data table. Each column contains the conditional predicted values for the corresponding response. The conditional predicted values are calculated using the best linear unbiased predictor (BLUP) coefficients.
Model Dialog
Shows the completed Fit Model launch window for the current analysis.
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.