Basic Analysis and Graphing - SAS

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220 Performing Simple Logistic Regression Chapter 7 The Logistic Report Figure 7.4 Example of a Logistic Report The Logistic report window contains the Logistic plot, the Iterations report, the Whole Model Test report, and the Parameter Estimates report. Note: The red triangle menu provides more options that can add to the initial report window. See “Logistic Platform Options” on page 224. Logistic Plot The logistic probability plot gives a complete picture of what the logistic model is fitting. At each x value, the probability scale in the y direction is divided up (partitioned) into probabilities for each response category. The probabilities are measured as the vertical distance between the curves, with the total across all Y category probabilities summing to 1.
Chapter 7 Performing Simple Logistic Regression 221 The Logistic Report Iterations Replace variables in the plot in one of two ways: swap existing variables by dragging and dropping a variable from one axis to the other axis; or, click on a variable in the Columns panel of the associated data table and drag it onto an axis. Related Information • “Additional Example of a Logistic Plot” on page 228 The Iterations report shows each iteration and the evaluated criteria that determine whether the model has converged. Iterations appear only for nominal logistic regression. Whole Model Test The Whole Model Test report shows if the model fits better than constant response probabilities. This report is analogous to the Analysis of Variance report for a continuous response model. It is a specific likelihood-ratio Chi-square test that evaluates how well the categorical model fits the data. The negative sum of natural logs of the observed probabilities is called the negative log-likelihood (–LogLikelihood). The negative log-likelihood for categorical data plays the same role as sums of squares in continuous data. Twice the difference in the negative log-likelihood from the model fitted by the data and the model with equal probabilities is a Chi-square statistic. This test statistic examines the hypothesis that the x variable has no effect on the responses. Values of the Rsquare (U) (sometimes denoted as R 2 ) range from 0 to 1. High R 2 values are indicative of a good model fit, and are rare in categorical models. Table 7.1 Description of the Whole Model Test Model (sometimes called Source) DF • The Reduced model only contains an intercept. • The Full model contains all of the effects as well as the intercept. • The Difference is the difference of the log likelihoods of the full and reduced models. Records the degrees of freedom associated with the model.
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Version 10 Basic Analysis and Graph
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USE, DATA OR PROFITS, WHETHER IN AN
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6 Options for Categorical Variables
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8 Nonparametric Bivariate Density R
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10 Example of the Power Option . .
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12 Statistical Details for the Logi
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14 Use Categorical Variables . . .
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16 Control Animation for Dynamic Bu
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18 Launch the Scatterplot Matrix Pl
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Contents Book Conventions. . . . .
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22 Learn about JMP Chapter 1 Book C
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24 Learn about JMP Chapter 1 Book C
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26 Learn about JMP Chapter 1 Additi
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28 Learn about JMP Chapter 1 Additi
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Contents Overview of the Distributi
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32 Performing Univariate Analysis C
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Contents Overview of the Fit Y by X
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90 Introduction to the Fit Y by X P
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Contents Example of Bivariate Analy
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94 Performing Bivariate Analysis Ch
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100 Performing Bivariate Analysis C
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130 Performing Oneway Analysis Chap
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270 Interactive Data Visualization
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Contents Example of the Chart Platf
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314 Creating Summary Charts Chapter
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340 Creating Overlay Plots Chapter
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Contents Example of a 3D Scatterplo
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354 Creating Three-Dimensional Scat
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Contents Example of a Contour Plot
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374 Creating Contour Plots Chapter
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Contents Example of a Dynamic Bubbl
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384 Creating Bubble Plots Chapter 1
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Contents Overview of Mapping . . .
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406 Creating Maps Chapter 16 Exampl
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418 Creating Maps Chapter 16 Backgr
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450 Creating Parallel Plots Chapter
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Contents Example of a Cell Plot. .
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460 Creating Cell Plots Chapter 18
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Contents Example of Tree Maps . . .
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468 Creating Tree Maps Chapter 19 E
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470 Creating Tree Maps Chapter 19 E
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472 Creating Tree Maps Chapter 19 T
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474 Creating Tree Maps Chapter 19 A
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486 Creating Scatterplot Matrices C
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Contents Example of a Ternary Plot
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496 Creating Ternary Plots Chapter
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504 References Becker, R.A. and Cle
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506 References Dunnett, C.W. (1955)
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508 References Hosmer, D.W. and Lem
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510 References McLachlan, G.J. and
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512 References Robertson, T., Wrigh
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516 Index examples 459, 463-464 lau
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518 Index Horizontal option 268, 32
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520 Index Proportion of Densities o
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522 Index examples 467-468, 473-482
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Basic Analysis and Graphing - SAS

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