Modeling and Multivariate Methods - SAS

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438 Performing Choice Modeling Chapter 16 Logistic Regression for Matched Case-Control Studies Figure 16.51 Parameter Estimate for Travel Time of Daganzo Data from One-Table Analysis Notice that the result is identical to that obtained for the two-table model, shown earlier in Figure 16.47. This chapter illustrates the use of the Choice Modeling platform with simple examples. This platform can also be used for more complex models, such as those involving more complicated transformations and interaction terms. Logistic Regression for Matched Case-Control Studies This section provides an example using the Choice platform to perform logistic regression on the results of a 1-1 matched-case control study. The data are from Hosmer and Lemeshow (2000). The purpose of the study is to identify risk factors associated with giving birth to a low birth weight baby ( Modeling > Choice. 3. Select the Select Data Table button. 4. Select Low Birth Weight as the profile data table. 5. Assign Low Birth Weight to the Profile ID role. 6. Assign Pair to the Grouping role. 7. Add the following columns as model effects: Weight of Mother, Race, Smoke During Pregnancy, History of Premature Labor, History of Hypertension, Uterine Irritability. 8. Deselect the Firth Bias-Adjusted Estimates checkbox. 9. Select Run Model. 10. When you are asked if this is a one-table analysis, answer Yes. 11. On the Choice Model red-triangle menu, select Profiler. The report is shown in Figure 16.52.
Chapter 16 Performing Choice Modeling 439 Logistic Regression for Matched Case-Control Studies Figure 16.52 Logistic Regression on Low Birth Weight Data Likelihod Ratio tests are given for each factor. Every factor, except Race, is a significant risk factor a low birth weight baby. Use the Prediction Profiler to visualize the impact of the factors on the response.
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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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Contents Book Conventions. . . . .
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Contents Launch the Fit Model Platf
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Contents Example Using Standard Lea
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158 Fitting Multiple Response Model
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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 Launch the Platform . . .
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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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654 Statistical Details Appendix A
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700 Index Stable 363 Stable Inverti
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Modeling and Multivariate Methods - SAS

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