Basic Analysis and Graphing - SAS

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152 Performing Oneway Analysis Chapter 5 Nonparametric Table 5.13 Descriptions of Nonparametric Tests Wilcoxon Test a Median Test van der Waerden Test Kolmogorov-Smirnov Test Exact Test Performs the test based on Wilcoxon rank scores. The Wilcoxon rank scores are the simple ranks of the data. The Wilcoxon test is the most powerful rank test for errors with logistic distributions. If the factor has two or more levels, the Kruskal-Wallis test is performed. The Wilcoxon test is also called the Mann-Whitney test. Performs the test based on Median rank scores. The Median rank scores are either 1 or 0, depending on whether a rank is above or below the median rank. The Median test is the most powerful rank test for errors with double-exponential distributions. Performs the test based on Van der Waerden rank scores. The Van der Waerden rank scores are the ranks of the data divided by one plus the number of observations transformed to a normal score by applying the inverse of the normal distribution function. The Van der Waerden test is the most powerful rank test for errors with normal distributions. Performs the test based on the empirical distribution function, which tests whether the distribution of the response is the same across the groups. Both an approximate and an exact test are given. This test is available only when the X factor has two levels. Provides options for performing exact versions of the Wilcoxon, Median, van der Waerden, and Kolmogorov-Smirnov tests. These options are available only when the X factor has two levels, and after the approximate test is requested.
Chapter 5 Performing Oneway Analysis 153 Nonparametric Table 5.13 Descriptions of Nonparametric Tests (Continued) Nonparametric Multiple Comparisons Provides several options for performing nonparametric multiple comparisons. These tests are based on ranks, and control for the overall alpha level, except for the Wilcoxon Each Pair test. The following tests are available: Wilcoxon Each Pair performs the Wilcoxon test on each pair, and does not control for the overall alpha level. This is the nonparametric version of the Each Pair, Student’s t option found on the Compare Means menu. Steel-Dwass All Pairs performs the Steel-Dwass test on each pair. This is the nonparametric version of the All Pairs, Tukey HSD option found on the Compare Means menu. Steel With Control compares each level to a control level. This is the nonparametric version of the With Control, Dunnett’s option found on the Compare Means menu. Dunn With Control for Joint Ranks compares each level to a control level, similar to the Steel With Control option. The Dunn method is different in that it computes ranks on all the data, not just the pair being compared. Dunn All Pairs for Joint Ranks performs a comparison of each pair, similar to the Steel-Dwass All Pairs option. The Dunn method is different in that it computes ranks on all the data, not just the pair being compared. See Dunn (1964) and Hsu (1996). a. For the Wilcoxon, Median, and Van der Waerden tests, if the X factor has more than two levels, a chi-square approximation to the one-way test is performed. If the X factor has two levels, a normal approximation to the two-sample test is performed, in addition to the chi-square approximation to the one-way test. Nonparametric Report Descriptions All nonparametric reports are described in the following tables: • Table 5.14 on page 153 • Table 5.15 on page 154 • Table 5.16 on page 155 Table 5.14 Descriptions of the Wilcoxon, Median, and Van der Waerden Tests Level Lists the factor levels occurring in the data.
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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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202 Performing Contingency Analysis
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Contents Overview of Logistic Regre
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218 Performing Simple Logistic Regr
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Contents Overview of the Matched Pa
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238 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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