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Modeling and Multivariate Methods - SAS

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Chapter 7 Performing Logistic Regression on Nominal <strong>and</strong> Ordinal Responses 211<br />

Logistic Fit Platform Options<br />

Figure 7.13 The Inverse Prediction Window <strong>and</strong> Table<br />

Clear the one to<br />

be predicted.<br />

See the appendix “Statistical Details” on page 651 for more details about inverse prediction.<br />

Save Comm<strong>and</strong>s<br />

If you have ordinal or nominal response models, the Save Probability Formula comm<strong>and</strong> creates new data<br />

table columns.<br />

If the response is numeric <strong>and</strong> has the ordinal modeling type, the Save Quantiles <strong>and</strong> Save Expected<br />

Values comm<strong>and</strong>s are also available.<br />

The Save comm<strong>and</strong>s create the following new columns:<br />

Save Probability Formula creates columns in the current data table that save formulas for linear<br />

combinations of the response levels, prediction formulas for the response levels, <strong>and</strong> a prediction<br />

formula giving the most likely response.<br />

For a nominal response model with r levels, JMP creates<br />

• columns called Lin[j] that contain a linear combination of the regressors for response levels<br />

j =1,2,...r -1<br />

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

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