Modeling and Multivariate Methods - SAS

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430 Performing Choice Modeling Chapter 16 Special Data Rules 7. Click on the disclosure icon for Subject Data > Select Data Table > Lung Cancer Choice.jmp > OK. 8. Add Smoker as the model effect. The Subject Data launch dialog box is shown in Figure 16.36. Figure 16.36 Subject Data for Lung Cancer Example 9. Uncheck Firth Bias-adjusted Estimates and Run Model. Choice Modeling results are shown in Figure 16.37. Figure 16.37 Choice Modeling Logistic Regression Results for the Cancer Data Compare these results with those of logistic regression under the Fit Model platform: • Open Lung Cancer.jmp in the sample data directory. • Select Analyze > Fit Model. Automatic specification of the columns is: Lung Cancer for Y, Count for Freq, and Smoker for Add under Construct Model Effects. The Nominal Logistic personality is automatically selected. • Click on Run Model. The nominal logistic fit for the data is shown in Figure 16.38.
Chapter 16 Performing Choice Modeling 431 Transforming Data Figure 16.38 Fit Model Nominal Logistic Regression Results for the Cancer Data Notice that the likelihood ratio chi-square test for Smoker*Lung Cancer in the Choice model matches the likelihood ratio chi-square test for Smoker in the Logistic model. The reports shown in Figure 16.37 and Figure 16.38 support the conclusion that smoking has a strong effect on developing lung cancer. See the “Performing Logistic Regression on Nominal and Ordinal Responses” chapter on page 197 for details. Transforming Data Transforming Data to Two Analysis Tables Although data are often in the Response/Profile/Subject form, the data are sometimes specified in another format that must be manipulated into the normalized form needed for choice analysis. For example, consider the data from Daganzo, found in Daganzo Trip.jmp. This data set contains the travel time for three transportation alternatives and the preferred transportation alternative for each subject. A partial listing of the data set is shown in Figure 16.39.
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6 Emphasis Options for Standard Lea
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8 Models with Crossed, Interaction,
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244 Performing Nonlinear Regression
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280 Creating Neural Networks Chapte
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Contents Launching the Platform. .
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296 Modeling Relationships With Gau
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306 Fitting Dispersion Effects with
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354 Performing Time Series Analysis
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Contents Principal Components. . .
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640 References Becker, R.A. and Cle
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654 Statistical Details Appendix A
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698 Index reliability analysis 453-
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700 Index Stable 363 Stable Inverti
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702 Index
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Modeling and Multivariate Methods - SAS

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