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## Book Description

Glenn Walker and Jack Shostak's Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is a thoroughly updated edition of the popular introductory statistics book for clinical researchers. This new edition has been extensively updated to include the use of ODS graphics in numerous examples as well as a new emphasis on PROC MIXED. Straightforward and easy to use as either a text or a reference, the book is full of practical examples from clinical research to illustrate both statistical and SAS methodology. Each example is worked out completely, step by step, from the raw data.

Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is an applications book with minimal theory. Each section begins with an overview helpful to nonstatisticians and then drills down into details that will be valuable to statistical analysts and programmers. Further details, as well as bonus information and a guide to further reading, are presented in the extensive appendices. This text is a one-source guide for statisticians that documents the use of the tests used most often in clinical research, with assumptions, details, and some tricks--all in one place.

2. PREFACE TO THE THIRD EDITION
3. PREFACE TO THE SECOND EDITION
4. PREFACE TO THE FIRST EDITION
5. 1. Introduction & Basics
1. 1.1 Statistics—the Field
2. 1.2 Probability Distributions
3. 1.3 Study Design Features
4. 1.4 Descriptive Statistics
5. 1.5 Inferential Statistics
6. 1.6 Summary
6. 2. Topics in Hypothesis Testing
1. 2.1 Significance Levels
2. 2.2 Power
3. 2.3 One-Tailed and Two-Tailed Tests
4. 2.4 p-Values
5. 2.5 Sample Size Determination
6. 2.6 Multiple Testing
1. Multiple Comparisons of Treatment Response
2. Multiple Response Variables
3. Interim Analyses
4. Multiple Studies
7. 2.7 Summary
7. 3. The Data Set TRIAL
8. 4. The One-Sample t-Test
1. 4.1 Introduction
2. 4.2 Synopsis
3. 4.3 Examples
4. 4.4 Details & Notes
9. 5. The Two-Sample t-Test
1. 5.1 Introduction
2. 5.2 Synopsis
3. 5.3 Examples
4. 5.4 Details & Notes
10. 6. One-Way ANOVA
1. 6.1 Introduction
2. 6.2 Synopsis
3. 6.3 Examples
4. 6.4 Details & Notes
11. 7. Two-Way ANOVA
1. 7.1 Introduction
2. 7.2 Synopsis
3. 7.3 Examples
1. "Mixed" Effects
2. Using PROC MIXED
4. 7.4 Details & Notes
12. 8. Repeated Measures Analysis
1. 8.1 Introduction
2. 8.2 Synopsis
3. 8.3 Examples
1. The PROC MIXED Approach
2. Missing Data
4. 8.4 Details & Notes
13. 9. The Crossover Design
1. 9.1 Introduction
2. 9.2 Synopsis
3. 9.3 Examples
4. 9.4 Details & Notes
14. 10. Linear Regression
1. 10.1 Introduction
2. 10.2 Synopsis
3. 10.3 Examples
1. Solution
2. SAS Analysis of Example 10.1
3. Solution
4. SAS Analysis of Example 10.2
4. 10.4 Details & Notes
15. 11. Analysis of Covariance
1. 11.1 Introduction
2. 11.2 Synopsis
3. 11.3 Examples
4. 11.4 Details & Notes
16. 12. The Wilcoxon Signed-Rank Test
1. 12.1 Introduction
2. 12.2 Synopsis
3. 12.3 Examples
4. 12.4 Details & Notes
17. 13. The Wilcoxon Rank-Sum Test
1. 13.1 Introduction
2. 13.2 Synopsis
3. 13.3 Examples
4. 13.4 Details & Notes
18. 14. The Kruskal-Wallis Test
1. 14.1 Introduction
2. 14.2 Synopsis
3. 14.3 Examples
4. 14.4 Details & Notes
19. 15. The Binomial Test
1. 15.1 Introduction
2. 15.2 Synopsis
3. 15.3 Examples
1. Solution
2. SAS Analysis of Example 15.1
4. 15.4 Details & Notes
20. 16. The Chi-Square Test
1. 16.1 Introduction
2. 16.2 Synopsis
3. 16.3 Examples
1. Solution
2. SAS Analysis of Example 16.1
3. SAS Analysis of Example 16.2
4. SAS Analysis of Example 16.3
4. 16.4 Details & Notes
21. 17. Fisher's Exact Test
1. 17.1 Introduction
2. 17.2 Synopsis
3. 17.3 Examples
4. 17.4 Details & Notes
22. 18. McNemar's Test
1. 18.1 Introduction
2. 18.2 Synopsis
3. 18.3 Examples
1. Solution
2. SAS Analysis of Example 18.1
3. Solution
4. SAS Analysis of Example 18.2
4. 18.4 Details & Notes
23. 19. The Cochran-Mantel-Haenszel Test
1. 19.1 Introduction
2. 19.2 Synopsis
3. 19.3 Examples
4. 19.4 Details & Notes
24. 20. Logistic Regression
1. 20.1 Introduction
2. 20.2 Synopsis
3. 20.3 Examples
1. Clustered Binomial Data
4. 20.4 Details & Notes
25. 21. The Log-Rank Test
1. 21.1 Introduction
2. 21.2 Synopsis
3. 21.3 Examples
4. 21.4 Details & Notes
26. 22. The Cox Proportional Hazards Model
1. 22.1 Introduction
2. 22.2 Synopsis
3. 22.3 Examples
4. 22.4 Details & Notes
27. 23. Exercises
28. A. Probability Tables
29. B. Common Distributions Used in Statistical Inference
30. C. Basic ANOVA Concepts
31. D. SS Types I, II, III, and IV Methods for an Unbalanced Two-Way Layout
1. D.1 SS Types Computed by SAS
2. D.2 How to Determine the Hypotheses Tested
3. D.3 Empty Cells
4. D.4 More Than Two Treatment Groups
5. D.5 Summary
32. E. Multiple Comparison Methods
1. E.1 Introduction
2. E.2 Multiple Comparisons of Means
3. E.3 Multiple Comparisons of Binomial Proportions
4. E.4 Summary
33. F. Data Transformations
34. G. SAS Code for Exercises in Chapter 23
35. H. Finding Adjusted Alphas for Interim Analyses−SAS Examples
36. I. Commonly Used Parameterizations in Logistic Regression Models
37. REFERENCES