Modeling and Multivariate Methods - SAS

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416 Performing Choice Modeling Chapter 16 Example: Valuing Trade-offs • Click on Response Data > Select Data Table > Other > OK and select Laptop Runs.jmp from the sample data directory. • Select Response as the Profile ID Chosen, Choice1 and Choice2 as the Profile ID Choices, Survey and Choice Set as the Grouping columns, and Person as Subject ID. The Response Data dialog box is shown in Figure 16.16. Figure 16.16 Response Data Dialog Box for Laptop Study • To run the model without subject effects, click on Run Model. • Choose Profiler from the red-triangle menu.
Chapter 16 Performing Choice Modeling 417 Example: Valuing Trade-offs Figure 16.17 Laptop Results Without Subject Effects Results of this study show that while all the factors are important, the most important factor in the laptop study is Hard Disk. The respondents prefer the larger size. Note that respondents did not think a price increase from $1000 to $1200 was important, but an increase from $1200 to $1500 was considered important. This effect is easily visualized by examining the factors interactively with the Prediction Profiler. Such a finding can have implications for pricing policies, depending on external market forces. To include subject effect for the laptop study, simply add to the Choice Modeling dialog box: • Under Subject Data, Select Data Table > Other > OK > Laptop Subjects.jmp. • Select Person as Subject ID and Gender and Job as the model effects. The Subject Data dialog box is shown in Figure 16.18.
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Version 10 Modeling and Multivariat
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INDIRECT OR CONSEQUENTIAL DAMAGES O
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6 Emphasis Options for Standard Lea
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8 Models with Crossed, Interaction,
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10 8 Analyzing Screening Designs Us
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12 Examining the Residuals . . . .
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14 Response Frequencies . . . . . .
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16 19 Analyzing Principal Component
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18 Interpreting the Profiles . . .
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20 Discriminant Analysis . . . . .
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Contents Book Conventions. . . . .
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Contents Launch the Fit Model Platf
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158 Fitting Multiple Response Model
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180 Fitting Generalized Linear Mode
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200 Performing Logistic Regression
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Contents Overview of the Screening
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232 Analyzing Screening Designs Cha
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Contents Introduction to the Nonlin
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244 Performing Nonlinear Regression
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Contents Overview of Neural Network
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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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Contents Introduction to Partitioni
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318 Recursively Partitioning Data C
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Contents Launch the Platform . . .
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354 Performing Time Series Analysis
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Contents Principal Components. . .
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484 Analyzing Principal Components
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Contents Introduction . . . . . . .
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494 Performing Discriminant Analysi
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Contents Introduction to Item Respo
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Contents Surface Plots . . . . . .
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538 Plotting Surfaces Chapter 23 La
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556 Visualizing, Optimizing, and Si
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640 References Becker, R.A. and Cle
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642 References Draper, N. and Smith
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646 References Matsumoto, M. and Ni
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648 References Rawlings, J.O. (1988
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650 References Umetrics (1995), Mul
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Contents The Response Models . . .
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654 Statistical Details Appendix A
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690 Index Birth Death Subset.jmp 46
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692 Index Ellipses Transparency 451
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694 Index test for curvature 46 Kru
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696 Index Customizing 267 Nonlinear
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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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