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Producing High-Quality Figures Using SAS/GRAPH® and ODS Graphics Procedures [Pehme köide]

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  • Formaat: Paperback / softback, 282 pages, kõrgus x laius: 234x156 mm, kaal: 520 g, 35 Tables, black and white; 12 Illustrations, color; 49 Illustrations, black and white
  • Ilmumisaeg: 06-Feb-2015
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 148220701X
  • ISBN-13: 9781482207019
Teised raamatud teemal:
Producing High-Quality Figures Using SAS/GRAPH® and ODS Graphics ProceduresSuurem pilt
  • Formaat: Paperback / softback, 282 pages, kõrgus x laius: 234x156 mm, kaal: 520 g, 35 Tables, black and white; 12 Illustrations, color; 49 Illustrations, black and white
  • Ilmumisaeg: 06-Feb-2015
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 148220701X
  • ISBN-13: 9781482207019
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781482207019.html
Märksõnad:
Create Top-Quality Figures Using SAS

Producing High-Quality Figures Using SAS/GRAPH® and ODS Graphics Procedures gives statisticians and SAS programmers practical guidance on presenting research data in high-quality figures that meet the publication requirements of academic institutions and various industries, such as pharmaceutical companies, agricultural businesses, and financial organizations.

Choose the Proper Graph Formats, Options, and Fonts

The book provides all the details on selecting the right figure formats, options, and fonts to produce high-quality figures. In-depth instructions and SAS programs using procedures in both SAS/GRAPH and ODS Graphics show how to generate sample figures in listing graphics formats and ODS document files. Each chapter includes practical examples and SAS programs. Readers can easily modify the SAS programs to develop high-quality figures to meet their own needs. For those unfamiliar with SAS programming and SAS Graphics, the author describes how to produce sample figures in SAS ODS Graphics designer, a convenient tool for generating figures without having to write SAS programs. The book also discusses how to produce figures in a SAS Enterprise Guide project.

Arvustused

"This is a nice reference for someone wanting to go beyond the basics of graphics, especially if they want to make one of the graph types discussed. While different subject areas are represented, most examples are medical in nature." David A. Dickey, Department of Statistics, North Carolina State University

"SAS programmers looking to master SAS graphs and produce high-quality, customized plots do not need to search any more. Producing High-Quality Figures Using SAS/GRAPH® and ODS Graphics Procedures has it all hands down. By showing traditional SAS graph procedures with new SAS graph procedures, readers can benefit from the comparisons and enhancements in the new SAS graph procedures. With his many years of industry experience, the author guides us down the difficult path with many graph examples such as forest and survival plots. This book is a must for any SAS programmer wanting to take advantage of the latest SAS options to produce high-quality plots." Sunil Gupta, Gupta Programming, SASSavvy.com

" very easily readable, understandable, and comprehensive for all levels of SAS experiences. this is one of the few SAS books that is pertinent to the daily life of a SAS programmer in the pharmaceutical or biotech industry." Tracy Turschman, Vertex Pharmaceuticals Incorporated

Preface xiii
Acknowledgments xvii
Author Biography xix
1 SAS Can Produce High-Quality Figures 1(8)
1.1 Introduction
1(1)
1.2 Two Sample Figures Produced in SAS with Different Quality
1(2)
1.3 Bitmap and Vector Format Figures
3(2)
1.3.1 Bitmap Format Graphics
3(1)
1.3.2 Vector Format Graphics
4(1)
1.4 Why Vector Format Figures?
5(1)
1.5 Publication Requirements for Art and Figure Preparation
5(2)
1.5.1 Taylor & Francis Group: Electronic Art Guidelines
5(1)
1.5.1.1 Vector Graphics Formats
6(1)
1.5.1.2 Bitmapped Graphics Formats
6(1)
1.5.2 Nature: Final Artwork
6(1)
1.5.3 Science: Preparing Your Art and Figures
7(1)
1.6 SAS Can Produce High-Quality Figures to Meet Publication Requirements
7(1)
1.7 References
7(2)
2 Principles of Producing High-Quality Figures in SAS 9(12)
2.1 Introduction
9(1)
2.2 SAS/GRAPH and ODS Graphics Procedures
9(2)
2.2.1 SAS/GRAPH Procedures
9(1)
2.2.2 SAS ODS Graphics Procedures
10(1)
2.2.3 SAS/GRAPH versus ODS Graphics Procedures
10(1)
2.3 Listing Output to Save Figures from One Procedure (PS, EPS, EMF, CGM, and so on)
11(1)
2.4 ODS Output to Save Figures from Several Procedures into a Document (PDF, RTF, and so on)
12(1)
2.5 GOPTIONS in SAS/GRAPH
13(3)
2.6 Software vs. Hardware Fonts
16(2)
2.6.1 Software Fonts
16(1)
2.6.2 Hardware Fonts
16(1)
2.6.3 Available Hardware Fonts for Listing Outputs
17(1)
2.6.4 Available Hardware Fonts for ODS Outputs (RTF, PDF)
18(1)
2.7 Controlling Titles and Footnotes in RTF Format Figure Files
18(1)
2.8 Adding Bookmarks in PDF Format Figure Files
19(1)
2.9 Setting Up Global Options and Macro Variables
19(1)
2.10 References
20(1)
3 Line Plots 21(30)
3.1 Introduction
21(1)
3.2 Application Examples
21(4)
3.2.1 A Simple Line Plot with Mean IOP Values by Time
23(1)
3.2.2 A Line Plot with SD Bar Displayed Together with the Mean IOP Values
23(1)
3.2.3 Line Plots with Maximum, Average, and Minimum Rates and Points for a 30-year Fixed-Rate Mortgage
24(1)
3.3 Producing the Sample Figures
25(7)
3.3.1 Data Structure and SAS Annotated Dataset
25(1)
3.3.2 Notes to SAS Programs
25(9)
3.3.2.1 Main Sections and Features of the First Program
27(3)
3.3.2.2 Main Features of the Second SAS Program
30(2)
3.4 Summary and Discussion
32(2)
3.5 References
34(1)
3.6 Appendix: SAS Programs for Producing the Sample Figures
34(17)
3.6.1 Line Plots for IOP Values
34(9)
3.6.2 Line Plots for Mortgage Rates and Points
43(8)
4 Scatter and Jittered Scatter Plots 51(24)
4.1 Introduction
51(1)
4.2 Application Examples
51(3)
4.2.1 Example 1: Scatter Plots with Mean Value Displayed
52(1)
4.2.2 Example 2: Scatter Plot with Mean Values and Reduction Reference Lines
52(1)
4.2.3 Example 3: Jittered Scatter Plots with IOP Values Displayed Side by Side
53(1)
4.3 Producing the Sample Figures
54(6)
4.3.1 Data Structure and SAS Annotated Dataset
54(1)
4.3.2 Notes to SAS Programs
54(23)
4.3.2.1 Dataset Simulation
56(1)
4.3.2.2 Data Analyses and Manipulation
56(1)
4.3.2.3 SAS/GRAPH Annotate Datasets
57(1)
4.3.2.4 Producing the Scatter Plots in GPLOT
58(1)
4.3.2.5 Producing the Scatter Plots in SGPLOT
59(1)
4.3.2.6 Producing Line-Up littered Scatter Plot
60(1)
4.4 Summary and Discussion
60(1)
4.5 References
61(1)
4.6 Appendix: SAS Programs for Producing the Sample Figures
62(13)
5 Line-Up tittered Scatter Plots 75(20)
5.1 Introduction
75(1)
5.2 Algorithms for Line-Up littered Scatter Plots
75(1)
5.3 Application Examples
76(1)
5.4 Producing the Sample Figures
77(8)
5.4.1 Data Structure and SAS Annotated Dataset
77(2)
5.4.2 Notes to SAS Programs
79(16)
5.4.2.1 Data Simulation
79(2)
5.4.2.2 Data Analyses and Manipulation
81(1)
5.4.2.3 Producing Sample Figures Using PROC GPLOT
82(2)
5.4.2.4 Producing Sample Figures Using PROC SGPLOT
84(1)
5.5 Summary and Discussion
85(1)
5.6 References
86(1)
5.7 Appendix: SAS Programs for Producing the Sample Figures
86(9)
6 Thunderstorm or Raindrop Scatter Plots 95(26)
6.1 Introduction
95(1)
6.2 Application Examples
95(5)
6.2.1 Example 1: Two IOPs on the y-Axis by CCT on the x-Axis
96(1)
6.2.2 Example 2: Baseline and Week 12 Mean Diurnal IOP on the y-Axis by Subjects Grouped by Investigator Sites on the x-Axis
96(1)
6.2.3 Example 3: Plant Tissue Nutrient Contents before and after Salinity Stress in Creeping Bentgrass
97(3)
6.3 Producing the Sample Figures
100(6)
6.3.1 Data Structure and SAS Annotated Dataset
100(1)
6.3.2 Notes to SAS Programs
100(7)
6.3.2.1 Main Sections and Features of the First Program
102(2)
6.3.2.2 Main Sections and Features of the Second Program
104(1)
6.3.2.3 Main Sections and Features of the Third Program
105(1)
6.4 Summary and Discussion
106(1)
6.5 References
106(1)
6.6 Appendix: SAS Programs for Producing the Sample Figures
107(14)
6.6.1 Thunderstorm Scatter Plots for Two Types of IOPs by Corresponding CCT
107(4)
6.6.2 Thunderstorm Scatter Plots for IOP at Baseline and Week 12 by Subject
111(6)
6.6.3 Raindrop Scatter Plots for Plant Nutrient Contents at Three Salinity Levels
117(4)
7 Spaghetti Plots 121(16)
7.1 Introduction
121(1)
7.2 Application Examples
121(2)
7.3 Producing the Sample Figures
123(6)
7.3.1 Data Structure and SAS Annotated Dataset
123(2)
7.3.2 Notes to SAS Programs
125(12)
7.3.2.1 Dataset Simulation and Manipulation
125(1)
7.3.2.2 Producing the Sample Figures Using the GPLOT and GREPLAY Procedures
125(2)
7.3.2.3 Producing the Sample Figures Using the SGPLOT and SGPANEL Procedures
127(2)
7.4 Summary and Discussion
129(1)
7.5 References
130(1)
7.6 Appendix: SAS Programs for Producing the Sample Figures
130(7)
8 Bar Charts 137(20)
8.1 Introduction
137(1)
8.2 Application Examples
137(2)
8.2.1 Example 1: Bar Chart of Drug Effects on IOP Reduction by Baseline IOP Categories
137(2)
8.2.2 Example 2: Stacked Bar Charts for Patient Drop-out Reasons by Treatment and Visit
139(1)
8.3 Producing the Sample Figures
139(5)
8.3.1 Data Structure
139(1)
8.3.2 Notes to SAS Programs
140(6)
8.3.2.1 Dataset Simulation (1st Program)
140(1)
8.3.2.2 Data Analyses and Manipulation (1st Program)
140(1)
8.3.2.3 Producing Bar Charts Using GPLOT and GREPLAY
141(1)
8.3.2.4 Producing Bar Charts Using SGPLOT and SGPANEL
142(2)
8.3.2.5 Bar Charts with Stacked and Cluster Groups (2nd Program)
144(1)
8.4 Summary and Discussion
144(1)
8.5 References
145(1)
8.6 Appendix: SAS Programs for Producing the Sample Figures
146(11)
8.6.1 Bar Charts
146(6)
8.6.2 Stacked Bar Charts
152(5)
9 Box Plots 157(18)
9.1 Introduction
157(1)
9.2 Application Examples
157(1)
9.2.1 Example: Box Plots for Drug Effects on IOP Reduction by Baseline IOP Categories
157(1)
9.3 Producing the Sample Figures
158(5)
9.3.1 Data Structure
158(1)
9.3.2 Notes to SAS Programs
158(17)
9.3.2.1 Dataset Simulation
158(1)
9.3.2.2 Data Analyses and Manipulation
159(1)
9.3.2.3 Producing the Sample Figures Using GPLOT and GREPLAY
160(1)
9.3.2.4 Producing the Sample Figures in SGPLOT and SGPANEL
161(1)
9.3.2.5 Producing Custom Box Plots with Specified Whisker Length in SGPLOT
162(1)
9.4 Understanding Box Plots
163(2)
9.5 Summary and Discussion
165(1)
9.6 References
166(1)
9.7 Appendix: SAS Programs for Producing the Sample Figures
166(9)
10 Forest Plots 175(20)
10.1 Introduction
175(1)
10.2 Application Examples
175(2)
10.2.1 Example 1: Mean Estimates and 95% CI for Treatment Difference at Each Post-baseline Visit and Hour
177(1)
10.2.2 Example 2: Relative Risk and 95% CI for Different Adverse Events
177(1)
10.3 Producing the Sample Figures
177(7)
10.3.1 Data Structure and SAS Annotated Dataset
177(1)
10.3.2 Notes to SAS Programs
178(19)
10.3.2.1 First Part Main Sections and Features
180(2)
10.3.2.2 Second Part Main Sections and Features
182(2)
10.4 Summary and Discussion
184(1)
10.5 References
184(1)
10.6 Appendix: SAS Programs for Producing the Sample Figures
185(10)
11 Survival Plots 195(12)
11.1 Introduction
195(1)
11.2 Application Examples
195(2)
11.3 Producing the Sample Figures
197(5)
11.3.1 Data Structure
197(1)
11.3.2 Notes to SAS Programs
197(10)
11.3.2.1 Producing Survival Plots Using the LIFETEST Procedure Directly
198(2)
11.3.2.2 Producing Survival Plots Using the SGPLOT Procedure with the Output Dataset from LIFETEST
200(2)
11.4 Summary and Discussion
202(1)
11.5 References
202(1)
11.6 Appendix: SAS Programs for Producing the Sample Figures
202(5)
12 Waterfall Plots and Histograms 207(16)
12.1 Introduction
207(1)
12.2 Application Examples
207(3)
12.2.1 Waterfall Plot: Change from Baseline in IOP for 50 Subjects
208(1)
12.2.2 Histogram Plot
208(2)
12.3 Producing the Sample Figures
210(4)
12.3.1 Data Structure and SAS Annotated Dataset
210(1)
12.3.2 Notes to SAS Programs
210(5)
12.3.2.1 Main Sections of the First Program
211(2)
12.3.2.2 Main Sections of the Second Program
213(1)
12.4 Summary and Discussion
214(1)
12.5 References
214(1)
12.6 Appendix: SAS Programs for Producing the Sample Figures
215(8)
12.6.1 Waterfall Plots
215(3)
12.6.2 Histograms
218(5)
13 Bland-Altman Plots for Agreement Analyses 223(10)
13.1 Introduction
223(1)
13.2 Agreement versus Correlation
223(2)
13.3 Application Example
225(1)
13.4 Producing the Sample Figures
225(2)
13.4.1 Data Structure
225(1)
13.4.2 Notes to SAS Programs
225(8)
13.4.2.1 Dataset Simulation and Analyses
226(1)
13.4.2.2 Producing the Sample Plots Using the GPLOT Procedure
226(1)
13.4.2.3 Producing the Sample Plots Using the SGPLOT Procedure
226(1)
13.5 Summary and Discussion
227(1)
13.6 References
227(1)
13.7 Appendix: SAS Programs for Producing the Sample Figures
227(6)
14 SAS ODS Graphic Designer 233(16)
14.1 Introduction
233(1)
14.2 SAS ODS Graphic Designer
233(1)
14.2.1 The Designer GUI
233(1)
14.2.2 The Graph Gallery
234(1)
14.3 Using the ODS Graphic Designer to Reproduce Some Figures in the Previous
Chapters
234(5)
14.3.1 Line-Up Jittered Scatter Plots
236(2)
14.3.2 Classification Box Plots
238(1)
14.4 Summary and Discussion
239(1)
14.5 References
240(1)
14.6 Appendix: SAS Programs for Producing the Datasets and Generated by the Designer
240(9)
14.6.1 The littered Scatter Plot: Codes Producing the Dataset
240(4)
14.6.2 The Tittered Scatter Plot: GTL Codes Generated by the Designer
244(1)
14.6.3 The Classification Box Plot: Codes for Producing the Dataset
245(3)
14.6.4 The Classification Box Plot: GTL Codes Generated by the Designer
248(1)
15 Producing Figures in the SAS Enterprise Guide Environment 249(8)
15.1 Introduction
249(1)
15.2 Create, Run, and Save an EG Project
249(3)
15.3 Server List
252(1)
15.4 Some Good Features and Notes for SAS EG
252(1)
15.5 Producing Graphics Directly in SAS EG Using the Point-and-Click Feature
253(2)
15.6 Summary and Discussion
255(1)
15.7 References
255(2)
Index 257
Charlie Chunhua Liu, PhD, is an associate director of biostatistics at Kythera Biopharmaceuticals Inc. in Westlake Village, California. Dr. Liu has been a SAS programmer and project statistician in several research institutions and pharmaceutical companies, including the U.S. Environmental Protection Agency (EPA), the National Institute of Statistical Sciences (NISS), the Washington University School of Medicine in St. Louis, Eli Lilly and Company, and Allergan Inc. He received a PhD in crop science and a masters in statistics from North Carolina State University.