Statistical Graphics Procedures by Example : Effective Graphs Using SAS

Sanjay Matange and Dan Heath's __Statistical Graphics Procedures by Example: Effective Graphs Using SAS__shows the innumerable capabilities of SAS Statistical Graphics (SG) procedures. The authors begin with a general discussion of the principles of effective graphics, ODS Graphics, and the SG procedures. They then move on to show examples of the procedures many features. The book is designed so that you can easily flip through it, find the graph you need, and view the code right next to the example. Among the topics included are how to combine plot statements to create custom graphs; customizing graph axes, legends, and insets; advanced features, such as annotation and attribute maps; tips and tricks for creating the optimal graph for the intended usage; real-world examples from the health and life sciences domain; and ODS styles. The procedures in __Statistical Graphics Procedures by Example__ are specifically designed for the creation of analytical graphs. That makes this book a must-read for analysts and statisticians in the health care, clinical trials, financial, and insurance industries. However, you will find that the examples here apply to all fields. Copyright 3 Contents 4 Preface 10 Chapter 1 Introduction 14 1.1 Principles of Effective Graphics 16 1.2 Automatic Graphs from SAS Procedures 23 1.3 Graph Template Language 24 1.4 Statistical Graphics Procedures 24 1.5 Organization of This Book 25 1.6 Data Sets and Custom Styles 27 1.7 Color and Gray-Scale Graphs 27 1.8 Effective Graphics and the Use of Decorative Skins 28 1.9 SAS 9.2 and SAS 9.3 Features 28 Chapter 2 Statistical Graphics Procedures 30 2.1 Key Concepts 32 2.2 SGPLOT Procedure 35 2.3 SGPANEL Procedure 37 2.4 Combining Statements 42 2.5 SGSCATTER Procedure 43 2.6 Styles and Their Usage 45 2.7 Template-Based Graphics vs. Device-Based Graphics 46 Chapter 3 Common Graphs 48 3.1 Introduction 50 3.2 Single-Cell Graphs 51 3.3 Classification Panels 68 3.4 Comparative and Matrix Graphs 70 Chapter 4 Basic Plots 72 4.1 Introduction 74 4.2 SGPLOT Procedure 75 4.5 Scatter Plots with Data Labels 87 4.6 Series Plot 91 4.7 Step Plot 97 4.8 Band Plot 102 4.9 Needle Plot 107 4.10 Vector Plot 110 4.11 VBarParm and HBarParm Plots (9.3) 113 4.12 Bubble Plot (9.3) 118 4.13 HighLow Plot (9.3) 121 4.14 Reference Lines 125 4.15 Parametric Line Plot (9.3) 128 4.16 Waterfall Chart (9.3) 130 4.17 Combining the Plots 133 Chapter 5 Fit and Confidence Plots 140 5.1 Introduction 142 5.2 Fit Plot Roles and Options 143 5.3 Regression Plot 144 5.4 Loess Plot 151 5.5 Penalized B-Spline Plot 158 5.6 Ellipse Plot 165 5.7 Combining the Plots 170 Chapter 6 Distribution Plots 172 6.1 Introduction 174 6.2 Histogram 175 6.3 Density Plot 179 6.4 Vertical Box Plot 182 6.5 Horizontal Box Plot 187 6.6 Combining the Plots 190 Chapter 7 Categorization Plots 192 7.1 Introduction 194 7.2 Categorization Plot Roles and Common Options 195 7.3 Vertical Bar Charts 196 7.4 Horizontal Bar Charts 204 7.5 Vertical Line Charts 211 7.6 Horizontal Line Charts 218 7.7 Dot Plots 225 7.8 Combining the Plots 231 Chapter 8 Axes, Legends, and Insets 232 8.1 Introduction 234 8.2 Linear Axis 236 8.3 Log Axis 238 8.4 Time Axis 240 8.6 Legends 243 8.7 Insets 245 Chapter 9 Annotation and Attribute Maps (SAS 9.3) 246 9.1 Annotation 248 9.2 Attribute Maps (9.3) 264 Chapter 10 Classification Panels 268 10.1 Introduction 270 10.2 SGPANEL Procedure 271 10.5 Paging of Large Panels 279 Chapter 11 Comparative and Matrix Plots 280 11.1 Introduction 282 11.2 SGSCATTER Procedure 282 11.3 PLOT Statement 283 11.4 COMPARE Statement 289 11.5 MATRIX Statement 294 Chapter 12 Health and Life Sciences Graphs 298 12.1 Introduction 300 12.2 Forest Plot 301 12.3 Forest Plot (9.3) 302 12.4 Survival Plot 303 12.5 Adverse Event Timeline 304 12.6 Adverse Event Timeline (9.3) 305 12.7 Maximum LFT Values by Treatment (9.3) 306 12.8 Median of Lipid Profile over Time by Treatment (9.3) 307 12.9 QTc Change from Baseline over Time by Treatment (9.3) 308 12.10 QTc Change Graph with Annotated “At Risk” Values (9.3) 309 12.11 QTc Change from Baseline over Time by Treatment 310 12.12 LFT Safety Panel, Baseline vs. Study 311 12.13 Immunology Profile by Treatment 312 12.14 Most Frequent On-Therapy Adverse Events by Frequency 313 12.15 LFT Patient Profile 314 12.16 Panel of LFT Values 315 12.17 Distribution of Eye Irritation Using PROC SGPANEL (9.3) 316 12.18 Distribution of Eye Irritation Using PROC SGPLOT (9.3) 317 12.19 Vital Signs by Time Point Name 318 12.20 Concomitant Medications 319 12.21 Creating a 2 x 2 Cell Graph Using PROC SGPLOT 320 Chapter 13 Business Graphs 322 13.1 Introduction 324 13.2 Stock Price and Volume Chart 325 13.3 Financial Trend and Bond Maturity Graph (9.3) 326 13.4 Danger of High P/E Ratios 327 13.5 Oil Consumption Trend by Country 328 13.6 Product Sales and Target Graph (9.3) 329 13.7 Social Network (9.3) 330 Chapter 14 Styles 332 14.1 Introduction 334 14.2 Using Styles 334 14.3 Style Elements 334 14.4 Using Style Elements 337 14.5 Style Element Usage Precedence 337 Chapter 15 ODS Destination and ODS Graphics Options 338 15.1 Introduction 340 15.2 ODS Destination Options 340 15.3 ODS Graphics Options 341 Chapter 16 Tips for Graph Output 344 16.1 Introduction 346 16.2 Creating Small Graphs for Use in Documents 346 16.3 Creating Large Graphs for Use in Presentations 347 16.4 Combining Graph Size and DPI 349 16.5 Impact of Graph Size on System Resources 349 Index 350 Sanjay Matange and Dan Heath's Statistical Graphics Procedures by Example: Effective Graphs Using SAS shows the innumerable capabilities of SAS Statistical Graphics (SG) procedures. The authors begin with a general discussion of the principles of effective graphics, ODS Graphics, and the SG procedures. They then move on to show examples of the procedures many features. The book is designed so that you can easily flip through it, find the graph you need, and view the code right next to the example. Among the topics included are how to combine plot statements to create custom graphs; customizing graph axes, legends, and insets; advanced features, such as annotation and attribute maps; tips and tricks for creating the optimal graph for the intended usage; real-world examples from the health and life sciences domain; and ODS styles. The procedures in Statistical Graphics Procedures by Example are specifically designed for the creation of analytical graphs. That makes this book a must-read for analysts and statisticians in the health care, clinical trials, financial, and insurance industries. However, you will find that the examples here apply to all fields. Annotation Shows the innumerable capabilities of SAS Statistical Graphics (SG) procedures. It begins with a general discussion of the principles of effective graphics, ODS Graphics, and the SG procedures, then moves on to show examples of the procedures' many features