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Publication date: 07/24/2024

Options for Nominal Fits

The following options are available in the Nominal Logistic Fit red triangle menu:

Plot Options

(Available only if the model consists of a single continuous effect.) The Plot Options menu contains the following options:

Show Points

Toggles the points in the Logistic Plot on or off.

Show Rate Curve

Enables you to compare the rate at various values of the effect variable with the fitted logistic curve. This option is useful only if you have several points for each value of the effect. In these cases, you get reasonable estimates of the rate at each value, and 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

Specifies the color of the plot curves.

Inverse Prediction

(Available only for two-level nominal responses.) Finds the x value that results in a specified probability. See the appendix “Statistical Details” for more information about inverse prediction.

Save Probability Formula

Saves new columns to the data table. The new columns contain formulas for linear combinations of the response levels, prediction formulas for the response levels, and a prediction formula that gives the most likely response.

For a nominal response model with r levels, JMP creates the following columns:

columns called Lin[j] that contain a linear combination of the regressors for response levels j = 1, 2, ... r - 1

a column called Prob[r], with a formula for the fit to the last level, r

columns called Prob[j] for j < r with a formula for the fit to level j

a column called Most Likely response name that selects the most likely level of each row based on the computed probabilities.

Image shown herePublish Probability Formulas

Creates probability formulas and saves 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.

Specify Profit Matrix

Enables you to specify profits or costs associated with correct or incorrect classification decisions. You can also specify the profit matrix entries using a probability threshold. See “Specify Profit Matrix” in Predictive and Specialized Modeling.

Decision Threshold

(Available only for binary responses.) Shows or hides Decision Thresholds reports for the training, validation, and test sets, if specified. Each report contains a graph of the distribution of fitted probabilities for each model, confusion matrices for each model, and classification graphs to compare the model fits. See “Decision Thresholds Report” in Predictive and Specialized Modeling for more information about the Decision Thresholds report.

Indicator Parameterization Estimates

(Available only when there are nominal columns among the model effects.) Shows or hides the Indicator Function Parameterization report. This report contains parameter estimates for the model where nominal 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 and chi-square values given in the Indicator Function Parameterization report differ from those in the Parameter Estimates report. This is because the estimates are estimating different model parameters.

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