Handbook of Statistical Analyses Using SAS, Second Edition

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Edition: 2nd
Format: Paperback
Pub. Date: 2001-08-21
Publisher(s): Chapman & Hall/
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Summary

Powerful software often comes, unfortunately, with an overwhelming amount of documentation. As a leading statistics software package, SAS is no exception. Its manuals comprise well over 10,000 pages and can intimidate, or at least bewilder, all but the most experienced users.A Handbook of Statistical Analyses using SAS, Second Edition comes to the rescue. Fully revised to reflect SAS Version 8.1, it gives a concise, straightforward description of how to conduct a range of statistical analyses. The authors have updated and expanded every chapter in this new edition, and have incorporated a significant amount of new material. The book now contains more graphical material, more and better data sets within each chapter, more exercises, and more statistical background for each method. Completely new topics include the following:· Data description and simple inference for categorical variables· Generalized linear models· Longitudinal data: Two new chapters discuss simple approaches, graphs, summary measure, and random effect modelsResearcher or student, new user or veteran, you will welcome this self-contained guide to the latest version of SAS. With its clear examples and numerous exercises, A Handbook of Statistical Analyses using SAS, Second Edition is not only a valuable reference, but also forms the basis for introductory courses on either SAS or applied statistics at any level, from undergraduate to professional.

Author Biography

Geoff Der is a statistician with the U.K. Medical Research Council, at the University of Glasgow, Scotland Brian S. Everitt is a professor at the Institute of Psychiatry, University of London, U.K.

Table of Contents

A Brief Introduction to SAS
1(34)
Introduction
1(1)
The Microsoft Windows User Interface
2(3)
The Editor Window
3(1)
The Log and Output Windows
4(1)
Other Menus
4(1)
The SAS Language
5(6)
All SAS Statements Must End with a Semicolon
6(1)
Program Steps
6(1)
Variable Names and Data Set Names
7(1)
Variable Lists
7(4)
The Data Step
11(7)
Creating SAS Data Sets from Raw Data
11(1)
The Data Statement
12(1)
The Infile Statement
12(1)
The Input Statement
13(4)
Reading Data from an Existing SAS Data Set
17(1)
Storing SAS Data Sets on Disk
17(1)
Modifying SAS Data
18(7)
Creating and Modifying Variables
18(3)
Deleting Variables
21(1)
Deleting Observations
21(1)
Subsetting Data Sets
22(1)
Concatenating and Merging Data Sets
22(1)
Merging Data Sets: Adding Variables
23(1)
The Operation of the Data Step
24(1)
The proc Step
25(1)
The proc Statement
25(1)
The var Statement
25(1)
The where Statement
25(1)
The by Statement
26(1)
The class Statement
26(1)
Global Statements
26(2)
ODS: The Output Delivery System
28(1)
SAS Graphics
28(4)
Proc gplot
28(3)
Overlaid Graphs
31(1)
Viewing and Printing Graphics
31(1)
Some Tips for Preventing and Correcting Errors
32(3)
Data Description and Simple Inference: Mortality and Water Hardness in the U.K.
35(22)
Description of Data
35(1)
Methods of Analysis
36(1)
Analysis Using SAS
36(21)
Exercises
55(2)
Simple Inference for Categorical Data: From Sandflies to Organic Particulates in the Air
57(22)
Description of Data
57(3)
Methods of Analysis
60(1)
Analysis Using SAS
61(18)
Cross-Classifying Raw Data
61(2)
Sandflies
63(3)
Acacia Ants
66(2)
Piston Rings
68(2)
Oral Contraceptives
70(2)
Oral Cancers
72(3)
Particulates and Bronchitis
75(3)
Exercises
78(1)
Multiple Regression: Determinants of Crime Rate in the United States
79(22)
Description of Data
79(2)
The Multiple Regression Model
81(2)
Analysis Using SAS
83(18)
Exercises
99(2)
Analysis of Variance I: Treating Hypertension
101(16)
Description of Data
101(1)
Analysis of Variance Model
102(1)
Analysis Using SAS
103(14)
Exercises
116(1)
Analysis of Variance II: School Attendance Amongst Australian Children
117(14)
Description of Data
117(2)
Analysis of Variance Model
119(3)
Type I Sums of Squares
120(1)
Type III Sums of Squares
120(2)
Analysis Using SAS
122(9)
Exercises
130(1)
Analysis of Variance of Repeated Measures: Visual Acuity
131(12)
Description of Data
131(1)
Repeated Measures Data
131(2)
Analysis of Variance for Repeated Measures Designs
133(1)
Analysis Using SAS
134(9)
Exercises
142(1)
Logistic Regression: Psychiatric Screening, Plasma Proteins, and Danish Do-It-Yourself
143(22)
Description of Data
143(3)
The Logistic Regression Model
146(1)
Analysis Using SAS
147(18)
GHQ Data
147(6)
ESR and Plasma Levels
153(5)
Danish Do-It-Yourself
158(6)
Exercises
164(1)
Generalised Linear Models: School Attendance Amongst Australian School Children
165(14)
Description of Data
165(1)
Generalised Linear Models
165(4)
Model Selection and Measure of Fit
168(1)
Analysis Using SAS
169(10)
Exercises
176(3)
Longitudinal Data I: The Treatment of Postnatal Depression
179(18)
Description of Data
179(2)
The Analyses of Longitudinal Data
181(1)
Analysis Using SAS
181(16)
Graphical Displays
184(4)
Response Feature Analysis
188(7)
Exercises
195(2)
Longitudinal Data II: The Treatment of Alzheimer's Disease
197(16)
Description of Data
197(2)
Random Effects Models
199(2)
Analysis Using SAS
201(12)
Exercises
212(1)
Survival Analysis: Gastric Cancer and Methadone Treatment of Heroin Addicts
213(24)
Description of Data
213(5)
Describing Survival and Cox's Regression Model
218(4)
Survival Function
218(1)
Hazard Function
219(1)
Cox's Regression
220(2)
Analysis Using SAS
222(15)
Gastric Cancer
222(7)
Methadone Treatment of Heroin Addicts
229(6)
Exercises
235(2)
Principal Components Analysis and Factor Analysis: The Olympic Decathlon and Statemetns about Pain
237(26)
Description of Data
237(2)
Principal Components and Factor Analyses
239(4)
Principal Components Analysis
239(2)
Factor Analysis
241(1)
Factor Analysis and Principal Components Compared
242(1)
Analysis Using SAS
243(20)
Olympic Decathlon
243(9)
Statements about Pain
252(9)
Exercises
261(2)
Cluster Analysis: Air Pollution in the U.S.A.
263(24)
Description of Data
263(2)
Cluster Analysis
265(1)
Analysis Using SAS
266(21)
Exercises
284(3)
Discriminant Function Analysis: Classifying Tibetan Skulls
287(18)
Description of Data
287(2)
Discriminant Function Analysis
289(2)
Analysis Using SAS
291(14)
Exercises
304(1)
Correspondence Analysis: Smoking and Motherhood, Sex and the Single Girl, and European Stereotypes
305(22)
Description of Data
305(2)
Displaying Contingency Table Data Graphically Using Correspondence Analysis
307(3)
Analysis Using SAS
310(17)
Boyfriends
310(5)
Smoking and Motherhood
315(4)
Are the Germans Really Arrogant?
319(6)
Exercises
325(2)
Appendix A: SAS Macro to Produce Scatterplot Matrices 327(4)
Appendix B: Answers to Selected Chapter Exercises 331(16)
References 347(4)
Index 351

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