Table of contents for A handbook of statistical analysis using SAS / authors, Geoff Der [and] Brian S Everitt.

Bibliographic record and links to related information available from the Library of Congress catalog.

Note: Contents data are machine generated based on pre-publication provided by the publisher. Contents may have variations from the printed book or be incomplete or contain other coding.


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Contents
Preface.............................................................................................................. xiii
Authors............................................................................................................... xv
1 Introduction to SAS .................................................................................. 1
1.1 Introduction....................................................................................... 1
1.2 User Interface..................................................................................... 2
1.2.1 Editor Window ...................................................................... 3
1.2.2 Log Window.......................................................................... 5
1.2.3 Output Window .................................................................... 5
1.2.4 Results Window..................................................................... 5
1.2.5 Explorer Window................................................................... 5
1.2.6 Some Other Menus................................................................ 6
1.3 SAS Language .................................................................................... 6
1.3.1 Program Steps ........................................................................ 7
1.3.2 Variable Names and Data Set Names..................................... 7
1.3.3 Variable Lists.......................................................................... 8
1.4 Reading Data¿The Data Step .......................................................... 9
1.4.1 Creating SAS Data Sets from Raw Data............................... 11
1.4.2 Data Statement .................................................................... 11
1.4.3 Infile Statement.................................................................... 11
1.4.4 Input Statement ................................................................... 13
1.4.4.1 List Input.............................................................. 13
1.4.4.2 Column Input....................................................... 14
1.4.4.3 Formatted Input.................................................... 14
1.4.4.4 Multiple Lines per Observation............................. 17
1.4.4.5 Multiple Observations per Line............................. 18
1.4.4.6 Delimited Data ..................................................... 18
1.4.4.7 Tab-Separated Data............................................... 18
1.4.4.8 Comma-Separated Data ........................................ 18
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1.4.5 Proc Import ..................................................................... 19
1.4.6 Reading Data from Other Programs
and Databases .................................................................. 19
1.4.7 Temporary and Permanent SAS Data
Sets¿SAS Libraries.......................................................... 20
1.4.8 Reading Data from an Existing SAS Data Set .................. 20
1.5 Modifying SAS Data ...................................................................... 21
1.5.1 Creating and Modifying Variables.................................... 21
1.5.2 Missing Values in Arithmetic Expressions ........................ 21
1.5.3 Deleting Variables ............................................................ 24
1.5.4 Deleting Observations ...................................................... 25
1.5.5 Subsetting Data Sets......................................................... 25
1.5.6 Concatenating Data Sets¿Adding Observation............... 26
1.5.7 Merging Data Sets¿Adding Variables ............................. 26
1.5.8 Operation of the Data Step.............................................. 27
1.6 Proc Step........................................................................................ 28
1.6.1 Proc Statement................................................................. 28
1.6.2 Var Statement .................................................................. 28
1.6.3 Where Statement ............................................................. 28
1.6.4 By Statement.................................................................... 29
1.6.5 Class Statement................................................................ 29
1.7 Global Statements .......................................................................... 29
1.7.1 Options............................................................................ 30
1.8 SAS Graphics ................................................................................. 31
1.8.1 xy Plots¿Proc sgplot ....................................................... 31
1.8.2 Summary Plots ................................................................. 32
1.8.3 Panel Plots ....................................................................... 33
1.9 ODS¿The Output Delivery System ............................................. 33
1.9.1 ODS Procedure Output................................................... 34
1.9.2 ODS Styles ...................................................................... 34
1.9.3 Saving Output in SAS Data Sets¿ODS Output............. 35
1.9.4 ODS Graphics ................................................................. 35
1.10 Enhancing Output ......................................................................... 37
1.10.1 Variable Labels ................................................................. 37
1.10.2 Value Labels¿SAS Formats............................................. 37
1.11 Some Tips for Preventing and Correcting Errors............................ 38
2 Data Description and Simple Inference: Mortality and Water
Hardness in the United Kingdom .......................................................... 41
2.1 Introduction................................................................................... 41
2.2 Methods of Analysis ....................................................................... 44
2.3 Analysis Using SAS ........................................................................ 44
Exercises.................................................................................................... 66
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3 Simple Inference for Categorical Data: From Sandflies to Organic
Particulates in the Air ............................................................................. 69
3.1 Introduction..................................................................................... 69
3.2 Methods of Analysis ......................................................................... 71
3.3 Analysis Using SAS .......................................................................... 73
3.3.1 Cross-Classifying Raw Data.................................................. 73
3.3.2 Sandflies ............................................................................... 75
3.3.3 Acacia Ants .......................................................................... 78
3.3.4 Piston Rings ......................................................................... 80
3.3.5 Oral Contraceptives.............................................................. 81
3.3.6 Oral Cancers ........................................................................ 83
3.3.7 Particulates and Bronchitis ................................................... 88
Exercises.................................................................................................... 90
4 Analysis of Variance I: Treating Hypertension ...................................... 93
4.1 Introduction..................................................................................... 93
4.2 Analysis of Variance Model.............................................................. 94
4.3 Analysis Using SAS .......................................................................... 95
Exercises.................................................................................................. 107
5 Analysis of Variance II: School Attendance among
Australian Children ............................................................................... 111
5.1 Introduction................................................................................... 111
5.2 Analysis of Variance Model............................................................ 111
5.2.1 Type I Sums of Squares ..................................................... 114
5.2.2 Type III Sums of Squares................................................... 114
5.3 Analysis Using SAS ........................................................................ 116
Exercises.................................................................................................. 124
6 Simple Linear Regression: Alcohol Consumption
and Cirrhosis Deaths and How Old Is the Universe? ......................... 127
6.1 Introduction................................................................................... 127
6.2 Simple Linear Regression ............................................................... 129
6.3 Analysis Using SAS ........................................................................ 131
6.3.1 Alcohol and Death from Cirrhosis ..................................... 131
6.3.2 Estimating the Age of the Universe.................................... 138
Exercises.................................................................................................. 141
7 Multiple Regression: Determinants of Crime Rate in States
of the United States............................................................................... 145
7.1 Introduction................................................................................... 145
7.2 Multiple Regression Model ............................................................ 148
7.3 Analysis Using SAS ........................................................................ 149
Exercises.................................................................................................. 163
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8 Logistic Regression: Psychiatric Screening, Plasma Proteins,
Danish Do-It-Yourself and Lower Back Pain .................................... 167
8.1 Description of Data.................................................................... 167
8.2 Logistic Regression Model.......................................................... 171
8.3 Analysis Using SAS .................................................................... 173
8.3.1 GHQ Data................................................................... 173
8.3.2 ESR and Plasma Levels ................................................ 178
8.3.3 Danish Do-It-Yourself.................................................. 184
8.3.4 Driving and Back Pain ................................................. 191
Exercises................................................................................................ 194
9 Generalised Linear Models: Polyposis and School Attendance
among Australian School Children..................................................... 197
9.1 Description of Data .................................................................... 197
9.2 Generalised Linear Models.......................................................... 199
9.2.1 Model Selection and Measure of Fit ............................. 201
9.3 Analysis Using SAS .................................................................... 202
9.3.1 School Attendance in Australian Children .................... 204
9.3.2 Analysing the FAP Data ............................................... 211
Exercises................................................................................................ 213
10 Generalized Additive Models: Burning Rubber and Air
Pollution in the United States............................................................ 215
10.1 Introduction............................................................................... 215
10.2 Scatterplots and Generalized Additive Models............................ 215
10.2.1 Scatterplot Smoothers................................................... 217
10.2.2 Additive and GAMs..................................................... 222
10.3 Analysis Using SAS .................................................................... 223
10.3.1 Scatterplot Smoothers for the Galaxy
Data in Chapter 6........................................................ 223
10.3.2 Fitting an Additive Model to the Tyre Wear
Data in Table 10.1....................................................... 227
10.3.3 Fitting a GAM to the Air Pollution Data..................... 229
Exercises................................................................................................ 237
11 Analysis of Variance of Repeated Measures Visual Acuity ................ 239
11.1 Description of Data.................................................................... 239
11.2 Repeated Measures Data ............................................................ 239
11.3 Analysis of Variance for Repeated Measures Designs.................. 240
11.3.1 Model for the Visual Acuity Data ................................ 241
11.4 Analysis Using SAS .................................................................... 242
Exercises................................................................................................ 252
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12 Longitudinal Data I: Treatment of Post-natal Depression ............... 255
12.1 Description of Data.................................................................... 255
12.2 Analyses of Longitudinal Data.................................................... 255
12.3 Analysis Using SAS .................................................................... 259
12.3.1 Graphical Displays ....................................................... 261
12.3.1.1 Separate Plots of Each Subject¿s
Response over Time.................................... 261
12.3.1.2 Box Plots of the Observations
at Each Time Point..................................... 261
12.3.1.3 Plot of Means and Standard Errors ............. 262
12.3.1.4 Scatterplot Matrix ....................................... 264
12.3.2 Response Feature Analysis ............................................ 265
Exercises................................................................................................ 273
13 Longitudinal Data II: Linear Mixed Models. Computerised
Delivery of Cognitive Behavioural Therapy¿Beat the Blues........... 277
13.1 Introduction............................................................................... 277
13.2 Linear Mixed Models for Longitudinal Data.............................. 278
13.2.1 Random Intercept Model............................................. 280
13.2.2 Random Intercept and Slope Model ............................ 280
13.3 Analysis Using SAS .................................................................... 281
Exercises................................................................................................ 294
14 Longitudinal Data III: Generalized Estimating Equations and
Generalized Mixed Models: Treating Toenail Infection.................... 295
14.1 Introduction............................................................................... 295
14.2 Methods for Analysing Longitudinal Data Where the Response
Variable Cannot Be Assumed to Have a Normal Distribution... 296
14.2.1 Marginal Models .......................................................... 297
14.2.2 Conditional Models ..................................................... 298
14.3 Analysis Using SAS .................................................................... 300
14.3.1 Fitting a Logistic Regression Model Assuming
Independence of the Responses .................................... 301
14.3.2 Using the GEE Approach on the Toenail Data............ 307
14.3.3 Random Effects Model for the Toenail Data ............... 310
Exercises................................................................................................ 314
15 Survival Analysis: Gastric Cancer, the Treatment of Heroin
Addicts and Heart Transplants........................................................... 317
15.1 Introduction............................................................................... 317
15.2 Describing Survival Data............................................................ 320
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15.2.1 Survival Function ......................................................... 320
15.2.2 Hazard Function .......................................................... 321
15.3 Cox¿s Regression ........................................................................ 322
15.3.1 Time-Varying Covariates.............................................. 325
15.3.2 Diagnostics for Cox¿s Regression .................................. 325
15.4 Analysis Using SAS .................................................................... 327
15.4.1 Gastric Cancer.............................................................. 327
15.4.2 Methadone Treatment of Heroin Addicts .................... 335
15.4.3 Heart Transplant Data ................................................. 341
Exercises................................................................................................ 347
16 Principal Components Analysis and Factor Analysis: Olympic
Decathlon and Statements about Pain............................................... 351
16.1 Introduction............................................................................... 351
16.2 Principal Components Analysis and Factor Analysis................... 356
16.2.1 Principal Components Analysis .................................... 357
16.2.2 Factor Analysis ............................................................. 358
16.2.3 Factor Analysis and Principal
Components Compared ............................................... 359
16.3 Analysis Using SAS .................................................................... 360
16.3.1 Olympic Decathlon...................................................... 360
16.3.2 Statements about Pain.................................................. 367
Exercises................................................................................................ 378
17 Cluster Analysis: Air Pollution in the United States ......................... 381
17.1 Introduction............................................................................... 381
17.2 Cluster Analysis.......................................................................... 383
17.3 Analysis Using SAS .................................................................... 384
Exercises................................................................................................ 406
18 Discriminant Function Analysis: Classifying Tibetan Skulls ............ 407
18.1 Description of Data.................................................................... 407
18.2 Discriminant Function Analysis ................................................. 409
18.3 Analysis Using SAS .................................................................... 411
Exercises................................................................................................ 422
19 Correspondence Analysis: Smoking and Motherhood,
Sex and the Single Girl, and European Stereotypes............................... 425
19.1 Description of Data.................................................................... 425
19.2 Displaying Contingency Table Data Graphically Using
Correspondence Analysis ............................................................ 426
19.3 Analysis Using SAS .................................................................... 429
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19.3.1 Boyfriends .................................................................... 429
19.3.2 Smoking and Motherhood ........................................... 435
19.3.3 Are the Germans Really Arrogant? ............................... 440
Exercises................................................................................................ 448
Appendix ............................................................................................... 451
Answers to Selected Exercises ................................................................ 451
References ............................................................................................. 459
Index...................................................................................................... 465

Library of Congress Subject Headings for this publication:

SAS (Computer file).
Mathematical statistics -- Data processing.