Basic Analysis and Graphing - SAS

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200 Performing Contingency Analysis Chapter 6 Cochran Armitage Trend Test Related Information • “Example of the Measures of Association Option” on page 211 Cochran Armitage Trend Test This Cochran Armitage Trend tests for trends in binomial proportions across the levels of a single variable. This test is appropriate only when one variable has two levels and the other variable is ordinal. The two-level variable represents the response, and the other represents an explanatory variable with ordered levels. The null hypothesis is the hypothesis of no trend, which means that the binomial proportion is the same for all levels of the explanatory variable. The test statistic and p-values given in this section are approximate. An exact version of the trend test is available. See “Exact Test” on page 200. Related Information • “Example of the Cochran Armitage Trend Test” on page 211 Exact Test The following table describes the exact versions of three of the tests available in the Contingency platform. Fisher’s Exact Test Performs Fisher’s Exact test for an r x c table. This is a test for association between two variables. Fisher’s exact test assumes that the row and column totals are fixed, and uses the hypergeometric distribution to compute probabilities. This test does not depend on any large-sample distribution assumptions. This means it is appropriate for situations where the Likelihood Ratio and Pearson tests become less reliable, like for small sample sizes or sparse tables. The report includes the following information: Table Probability (P) gives the probability for the observed table. This is not the p-value for the test. Two-sided Prob ≤ P test. gives the p-value for the two-sided For 2x2 tables, the Fisher’s Exact test is automatically performed. See “Tests” on page 193.
Chapter 6 Performing Contingency Analysis 201 Additional Examples of the Contingency Platform Exact Cochran Armitage Trend Test Exact Agreement Test Performs the exact version of the Cochran Armitage Trend Test. This test is available only when one of the variables has two levels. For more details about the trend test, see “Cochran Armitage Trend Test” on page 200. Performs an exact test for testing agreement between variables. This is an exact test for the Kappa statistic. This is available only when the two variables have the same levels. For more details about agreement testing, see “Agreement Statistic” on page 197. Additional Examples of the Contingency Platform This section contains additional examples using the options in the Contingency platform. Example of Analysis of Means for Proportions This example uses the Office Visits.jmp sample data table, which records late and on-time appointments for six clinics in a geographic region. 60 random appointments were selected from 1 week of records for each of the six clinics. To be considered on-time, the patient must be taken to an exam room within five minutes of their scheduled appointment time. Examine the proportion of patients that arrived on-time to their appointment. 1. Open the Office Visits.jmp sample data table. 2. Select Analyze > Fit Y by X. 3. Select On Time and click Y, Response. 4. Select Clinic and click X, Factor. 5. Select Frequency and click Freq. 6. Click OK. 7. From the red triangle menu next to Contingency Analysis, select Analysis of Means for Proportions. 8. From the red triangle menu next to Analysis of Means for Proportions, select Show Summary Report.
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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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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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94 Performing Bivariate Analysis Ch
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100 Performing Bivariate Analysis C
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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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340 Creating Overlay Plots Chapter
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354 Creating Three-Dimensional Scat
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374 Creating Contour Plots Chapter
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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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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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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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