Basic Analysis and Graphing - SAS

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194 Performing Contingency Analysis Chapter 6 Analysis of Means for Proportions Table 6.4 Description of the Tests Report (Continued) Rsquare (U) Test Prob>ChiSq Portion of the total uncertainty attributed to the model fit. • An R 2 of 1 means that the factors completely predict the categorical response. • An R 2 of 0 means that there is no gain from using the model instead of fixed background response rates. For more information, see “Statistical Details for the Tests Report” on page 213. Lists two Chi-square statistical tests of the hypothesis that the response rates are the same in each sample category. For more information, see “Statistical Details for the Tests Report” on page 213. Lists the probability of obtaining, by chance alone, a Chi-square value greater than the one computed if no relationship exists between the response and factor. If both variables have only two levels, Fisher’s exact probabilities for the one-tailed tests and the two-tailed test also appear. Fisher’s Exact Test This report gives the results of Fisher’s exact test for a 2x2 table. The results appear automatically for 2x2 tables. For more details about Fisher’s exact test, and for details about the test for r x c tables, see “Exact Test” on page 200. Analysis of Means for Proportions If the response has two levels, you can use this option to compare response proportions for the X levels to the overall response proportion. This method uses the normal approximation to the binomial. Therefore, if the sample sizes are too small, a warning appears in the results. Note: For a description of Analysis of Means methods, see the document by Nelson, Wludyka, and Copeland (2005). For a description of the specific Analysis of Means for Variances method, see the paper by Wludyka and Nelson (1997). Table 6.5 Descriptions of the Analysis of Means for Proportions Options Set Alpha Level Show Summary Report Switch Response Level for Proportion Selects the alpha level used in the analysis. Produces a report that shows the response proportions with decision limits for each level of the X variable. The report indicates whether a limit has been exceeded. Changes the response category used in the analysis.
Chapter 6 Performing Contingency Analysis 195 Correspondence Analysis Table 6.5 Descriptions of the Analysis of Means for Proportions Options (Continued) Display Options Shows or hides the decision limits, decision limit shading, center line, and needles. Related Information • “Example of Analysis of Means for Proportions” on page 201 Correspondence Analysis Correspondence analysis is a graphical technique to show which rows or columns of a frequency table have similar patterns of counts. In the correspondence analysis plot, there is a point for each row and for each column. Use Correspondence Analysis when you have many levels, making it difficult to derive useful information from the mosaic plot. Understanding Correspondence Analysis Plots The row profile can be defined as the set of rowwise rates, or in other words, the counts in a row divided by the total count for that row. If two rows have very similar row profiles, their points in the correspondence analysis plot are close together. Squared distances between row points are approximately proportional to Chi-square distances that test the homogeneity between the pair of rows. Column and row profiles are alike because the problem is defined symmetrically. The distance between a row point and a column point has no meaning. However, the directions of columns and rows from the origin are meaningful, and the relationships help interpret the plot. Correspondence Analysis Options Use the options in the red triangle menu next to Correspondence Analysis to produce a 3-D scatterplot and add column properties to the data table. Table 6.6 Descriptions of the Correspondence Analysis Options 3D Correspondence Analysis Save Value Ordering Produces a 3-D scatterplot. Takes the order of the levels sorted by the first correspondence score coefficient and makes a column property for both the X and Y columns. The Details Report The Details report contains statistical information about the correspondence analysis and shows the values used in the plot.
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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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244 Comparing Paired Data Chapter 8
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246 Comparing Paired Data Chapter 8
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Contents Example of Bootstrapping .
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250 Bootstrapping Chapter 9 Example
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252 Bootstrapping Chapter 9 Unstack
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254 Bootstrapping Chapter 9 Analysi
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Contents Overview of Graph Builder
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258 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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Contents Example of an Overlay Plot
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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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Contents Example of a Parallel Plot
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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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Contents Example of a Scatterplot M
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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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514 References Wadsworth, H. M., St
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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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