Modeling and Multivariate Methods - SAS

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436 Performing Choice Modeling Chapter 16 Transforming Data Figure 16.47 Parameter Estimate for Travel Time of Daganzo Data i The negative coefficient implies that increased travel time has a negative effect on consumer utility or satisfaction. The likelihood ratio test result indicates that the Choice model with the effect of Travel Time is significant. Transforming Data to One Analysis Table Rather than creating two or three tables, it can be more practical to transform the data so that only one table is used. For the one-table format, the subject effect is added as above. A response indicator column is added instead of using three different columns for the choice sets (Choice1, Choice2, Choice3). The transformation steps for the one-table scenario include: • Create or open Stacked Daganzo.jmp from the steps shown in Transforming Data to Two Analysis Tables. • Add a new column labeled Response and right-click on the column. Select Formula. • Select Conditional > If from the formula editor and select the column Choice Mode for the expression. • Type “=” and select Mode. • Type 1 for the Then Clause and 0 for the Else Clause. Click OK. The completed formula should look like Figure 16.48. Figure 16.48 Formula for Response Indicator for Stacked Daganzo Data • Subset the data table by selecting Subject, Travel Time, and Response and then select Tables > Subset. Select Selected Columns and click OK. A partial listing of the new data table is shown in Figure 16.49.
Chapter 16 Performing Choice Modeling 437 Transforming Data Figure 16.49 Partial Table of Stacked Daganzo Data Subset • Select Analyze > Modeling > Choice to open the launch dialog box and specify the model as shown in Figure 16.50. Figure 16.50 Choice Dialog Box for Subset of Stacked Daganzo Data for One-Table Analysis • Select Run Model. A pop-up dialog window asks if this is a one-table analysis with all the data in the Profile Table. Select Yes to obtain the parameter estimate expressing the utility Travel Time coefficient, shown in Figure 16.51.
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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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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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158 Fitting Multiple Response Model
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232 Analyzing Screening Designs Cha
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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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318 Recursively Partitioning Data C
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354 Performing Time Series Analysis
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Contents The Categorical Platform .
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Contents Surface Plots . . . . . .
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640 References Becker, R.A. and Cle
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648 References Rawlings, J.O. (1988
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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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