For the latest version of JMP Help, visit JMP.com/help.


Basic Analysis > Logistic Analysis > Logistic Platform Options
Publication date: 05/05/2023

Logistic Platform Options

The Logistic Fit red triangle menu contains options for the Logistic plot and the Logistic Fit report.

Note: The Fit Group menu appears only if you have specified multiple Y or multiple X variables. Use the Fit Group menu options to arrange reports or order them by RSquare. See “Fit Group Options” in Fitting Linear Models.

The Logistic Fit red triangle menu contains the following options:

Odds Ratios

(Available only for a response with two levels.) Adds or removes columns that contain odds ratios to the Parameter Estimates report. See Statistical Details for Odds Ratios in Fitting Linear Models.

Inverse Prediction

(Available only for two-level nominal responses.) Enables you to predict values of the predictor variable for one or more values of the response variable. See Inverse Prediction.

Logistic Plot

Shows or hides the logistic plot. See Logistic Plot.

Plot Options

Contains the following options that affect the logistic plot:

Show Points

Shows or hides the points in the logistic plot.

Show Rate Curve

Shows or hides the rate curve in the logistic plot. The rate curve is useful only if you have several points for each value of the X variable. In these cases, you get reasonable estimates of the rate at each value, and you can compare this rate with the fitted logistic curve. To prevent too many degenerate points, usually at zero or one, JMP shows only the rate value if there are at least three points at the x-value.

Line Color

Enables you to select the color of the plot curves.

ROC Curve

Shows or hides the Receiver Operating Characteristic (ROC) curve for the model. The ROC curve is a plot of sensitivity versus (1 - specificity) for each value of the X variable. See ROC Curves.

Lift Curve

Shows or hides a lift curve for the model. A lift curve shows the predictive ability of the model. The lift curve plots the lift versus the portion of the observations. The lift curve contains a point for each unique predicted probability value. Each predicted probability of a response level defines a portion of the observations that have a predicted probability greater than or equal to the unique predicted probability value. For a particular level of the response, the lift value is the ratio of the proportion of observed responses in that portion to the overall proportion of observed responses. See Lift Curve in Predictive and Specialized Modeling for more information about lift curves.

Save Probability Formula

Saves new columns to the data table. The new columns contain the formula for the probability that is predicted by the model. The new columns contain the following:

formulas for linear combinations (typically called logits) of the factor variable

prediction formulas for the response level probabilities

a prediction formula for the most likely response

See Local Data Filters in JMP Reports, Redo Menus in JMP Reports, Save Platform Preferences, 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.

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).