A Juxtaposition of Tables and Graphs Using SAS /GRAPH Procedures

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1 A Juxtaposition of Tables and Graphs Using SAS /GRAPH Procedures Suhas R. Sanjee, MaxisIT Inc., Edison, NJ Sheng Zhang, Merck and Co., Upper Gwynedd, PA ABSTRACT Graphs provide high-impact visuals that enable decision makers to gain a quick understanding of critical business issues. However, graphs do not always convey all the details the reviewer wants; hence a corresponding table needs to be provided. Having relevant tables and annotations as part of a graph allows the reviewer to formulate appropriate decisions. The proposed method uses procedures in SAS/GRAPH to include tables as one of the panels of a multi-panel graph. Often it is required to create multiple graphs from the same data for different interpretations. While each graph by itself is useful, seeing all of the graphs on the same page is even more helpful. Multi-panel graphs enable reviewers to compare the performance of two treatment groups/periods. This article starts by introducing PROC GRE- PLAY. PROC GREPLAY enables display of different graphs in a single page. Then, a method to convert a table to graph object using PROC GPRINT is presented. The GPRINT procedure can be used to create graphics output from tabular material, reports, or any external text file produced by the SAS System. The converted graph containing the table is then combined with the corresponding graph using PROC GREPLAY. This process is illustrated with a graph and table generated to present the results of longitudinal data analysis. The resulting graph and table can be displayed on individual panels of a multi-panel graph. Finally, a method to juxtapose correlation statistics and plots using GSLIDE and GREPLAY procedures is presented. INTRODUCTION The goal of this paper is to demonstrate the use of SAS/GRAPH procedures to juxtapose tables and graphs to produce highly effective reports and starts by introducing the SAS/GRAPH procedures: GREPLAY, GPRINT and GSLIDE. In the subsequent section, two examples are presented which use these procedures to juxtapose tables and graphs to effectively communicate business ideas to reviewers. PROC GREPLAY Graphs generated using SAS/GRAPH procedures are stored in catalog files which are special files for storing different elements of SAS-like graphs, formats, macros etc. The GREPLAY procedure is used to replay and manage SAS graphs stored in SAS catalog files. It is a powerful tool which can be used for creating multi-panel graphs. The GREPLAY procedure also allows for the creation of customized templates. Sample code in Fig 1 illustrates definition of a template to replay two graphs one below the other. The options LLX=, LLY=, LRX=, LRY=, ULX=, ULY=, URX=, and URY= in the TDEF statement specify the X and Y coordinate values of the panels. Coordinate values less than 0 and greater than 100 can be specified for these options in order to zoom in on Fig 1: Example Code to define templates PROC GREPLAY TC=sashelp.tamplate NOFS; /* define template to display two graphs one below the other */ TDEF g2 DES='Vertical Graphs' /* Upper panel */ 1/LLX=0 LLY=50 ULX=0 ULY=100 URX=100 URY=100 LRX=100 LRY=50 /* LOWER PANEL */ 2/LLX=0 LLY=0 ULX=0 ULY=50 URX=100 URY=50 LRX=100 LRY=0; /* assign template */ TEMPLATE g2; Fig 2: Example Code to create multi-panel graphs PROC GREPLAY IGOUT=work.gseg TC=sashelp.template TEMPLATE=g2 NOFS; TREPLAY 1:Gplot1 2:Gplot2; Fig 3: Example Code for GPRINT GOPTIONS FTEXT='SAS Monospace' DEVICE=sasbmp HPOS=60; PROC GPRINT FILEREF=summary NAME='G2'; 1

2 the specific area of graphics output. Sample code presented in Fig 2 illustrates the use of the GREPLAY procedure in creating a multi-panel graph. The option TC = in the PROC GREPLAY statement is used to specify the SAS catalog. Gplot1, Gplot2 specified in TREPLAY statement are the two graphs generated using any SAS/GRAPH procedures. Numbers 1 and 2 specify the panel used for replaying each graph. PROC GPRINT The GPRINT procedure can be used to convert information in any list file produced by the SAS system to a SAS graph object. GPRINT can be used with the TABULATE procedure with appropriate options for FORMCHAR and DEVICE to import tables with a solid border into graph objects. Hexadecimal values that correspond to the border characters must be specified with the FORMCHAR option. In addition to this, it should be ensured that specified characters must exist in a hardware font available on the output device. It is also important to use a uniform font to avoid column alignment problems. The sample code to convert a list file to a graph object is given in Fig 3. "Summary" is the file reference to the list file. PROC GSLIDE The GSLIDE procedure is used to produce graphics output consisting of text and straight lines generated by TI- TLE, FOOTNOTE, and NOTE statements. The GSLIDE procedure can be used for creating text slides used in presentations. Text slides can also be overlaid on other graphics output using PROC GREPLAY. The sample code in Fig 4 creates a text slide with the text "Timepoint1" with a red colored frame. Fig 4: Example Code to Create Text Slide Using PROC GSLIDE PROC GSLIDE BORDER CFRAME=red NAME="cslide11" WFRAME=4; NOTE HEIGHT=10 JUSTIFY=center "Timepoint1" ; ILLUSTRATIONS The procedures GREPLAY, GPRINT and GSLIDE are illustrated with the help of two examples to show how SAS/GRAPH procedures can be used to juxtapose tables/text and graphs. The input dataset used in these illustrations is assumed to be from a hypothetical longitudinal study in which the subjects are randomized into three treatment groups and measurements are taken at multiple timepoints for each subject. The dataset contains one observation per subject per timepoint and hence is vertical in structure. Every subject has measurements taken at five different timepoints. ILLUSTRATION 1: JUXTAPOSITION OF TABLE AND PLOT This illustration shows the use of TABULATE, GPRINT, GPLOT and GREPLAY procedures for placing a table and a graph side by side so that information is conveyed more effectively. This involves the following four major steps: Step 1: Create Box plot using PROC GPLOT Box plot showing the distribution of measurements at all five timepoints for all three treatment groups is produced using the GPLOT procedure. Step 2: Create Summary Table using PROC TABULATE A summary table is generated using PROC TABULATE with appropriate hexadecimal values specified for FORMCHAR= option. The generated table is then stored in a list file using PROC PRINTTO. Step 3: Convert Table to Graph Using PROC GPRINT Procedure GPRINT is used to read the list file generated in Step 2 and to convert the table to a graph object. Appropriate values must be specified for DEVICE= option and FTEXT= option to make sure the font mentioned for the output device contains the hexadecimal value mentioned in FORMCHAR= option in the previous step. Step 4: Putting the two graphs together using PROC GREPLAY The two graphs produced in Steps 2 and 3 are combined using the GREPLAY procedure. 2

3 The SAS program for this illustration is presented in Fig 5 with detailed comments for each step. The output graph is shown in Fig 6. Fig 5: SAS Code for Illustration 1 *- Step 01: Create Box plot using PROC GPLOT --*; filename fileref 'C:\illustration1.cgm'; goptions reset=all device = cgmof97p gsfname = fileref gsfmode = replace reset = symbol colors = (black); **** SET SYMBOL DEFINITIONS; symbol1 width = 28 bwidth = 3 color = green line = 1 value = none interpol = BOXJT00 mode = include; symbol2 width = 28 bwidth = 3 color = red line = 1 value = none interpol = BOXJT00 mode = include; symbol3 width = 28 bwidth = 3 color = blue line = 1 value = none interpol = BOXJT00 mode = include; **** DEFINE THE LEGEND ; legend1 frame label = (height = 1.5 justify = right 'Treatment:' ) value = (height = 1.5) down=3 position = (top right inside); **** DEFINE VERTICAL AND VERTICAL AXES OPTIONS.; axis1 label=(h=2 rotate=0 angle=90 "Result") value = (h = 1.5 ) minor = (n = 3) order = (0 to.20 by.02); axis2 label = (h = 2 "Visit") value = (h = 1 "T1" "T2" "T3" "T4" "T5") order = (1 to 5 by 1) offset = (2cm, ) minor = none; **** CREATE BOX PLOT.; proc gplot data = datadir.simdatafin; plot result* ptimepnt = trtcd /vaxis = axis1 haxis = axis2 legend=legend1; format trtcd trtcd.; title1 h = 2 font = "TimesRoman" "Figure X.X"; title2 h = 2 font = "TimesRoman" "Timepoints by Treatment"; quit; *- Step 02: Create summary Table using PROC Tabulate -*; filename summary 'c:\summary.txt'; *Call printto procedure to store tabuate output in a list file; proc printto print=summary new; *Specify appropriate option for FORMCHAR; options formchar=' a8b8c2b3d7c2d2f5c3c3e2a'x nodate center nonumber; goptions hpos=40; proc tabulate data=datadir.simdatafin; var result; class trtcd time; table trtcd="", mean='' * result = "Mean Result"*F=6.2 * timepnt='' /box="treatment"; format trtcd trtcd. time; proc printto; 3

4 Fig 5: SAS Code for Illustration 1 continued. *- Step 03: Convert Table to Graph using PROC GPRINT -*; goptions ftext='sas Monospace' device=sasbmp hpos=60; title1 'Treatment Summary' h=10; footnote1 T1,T2,T3,T4 and T5 refer to Timepoints 1 through 5 respectively; proc gprint fileref=tot name='g2'; quit; *- Step 04: Putting the two graphs together using PROC GREPLAY -*; goptions ftext=swissu hpos=70 vpos=175 device=cgmof97p; proc greplay igout=work.gseg tc=sashelp.templt template=v2 nofs; treplay 1:gplot 2:g2; quit; Fig 6: Output Graph From Illustration 1 4

5 ILLUSTRATION 2: LATTICE PLOT FOR CORRELATION ANALYSIS This section uses only the first three timepoints of the input dataset described above. PROC CORR is used to get the Pearson correlation coefficients between each timepoint. The correlation coefficient, p-value and scatter plot are presented in a single table/graph and provide all the information needed at the same place making it easier for reviewers to make decisions. The input dataset is the first subset to retain only the first three timepoints. The dataset is then transposed to get three variables: timepoint1, timepoint2 and timepoint3. The data manipulation part is not dealt with in detail here since it is not the focus of the paper. The procedure for generating a lattice plot for correlation analysis involves four major steps: Step 1: Get correlation statistics The Pearson correlation statistics generated from PROC CORR is stored into a dataset using ODS. The code Fig 7: Code to get Correlation Coefficients ODS OUTPUT PearsonCorr=pcoff; PROC CORR DATA = transdata; VAR timepoint1 timepoint2 timepoint3; RUN; ODS OUTPUT CLOSE; Fig 8: Code to generate correlation plots PROC GPLOT DATA=transdata; PLOT timepoint1*timepoint2 timepoint2*timepoint3 timepoint1*timepoint3; RUN;QUIT; used for this step is as shown in Fig 7. The correlation statistics are then assigned to macro variables coefs&i&j and pcoefs&i&j where the macro variables i and j range from 1 to 3. These macro variables are passed to PROC GSLIDE to create text slides. Step 2: Generate correlation plots using PROC GPLOT Three scatter plots are obtained using PROC GPLOT. The plots produced by timepoint1*timepoint2 and timepoint2*timepoint1 contain the same information. Hence only one plot is generated for each combination of timepoints. DEVICE=CGMOF97L is used for this step. The code used for this step is as shown in Fig 8. Step 3: Generate text slides with panel labels and correlation statistics The code snippet in Fig 9 is used in a macro within a %DO loop with index variable i varying from 1 to 3 to produce three text slides with panel labels. Code snippet in Fig 10 is used in a macro within two nested %DO loops in which both index variables vary from 1 to 3. Six slides are generated with correlation statistics out of which only three are used since correlation statistics are symmetrical in nature. Fig 9: Code to generate slides with panel labels PROC GSLIDE BORDER CFRAME=red NAME="cslide&i&i" WFRAME=4; NOTE HEIGHT=20; NOTE HEIGHT=10 JUSTIFY=center "Timepoint&i" ; Fig 10: Code to generate slides with correlation statistics PROC GSLIDE BORDER NAME="cslide&i&n" WFRAME=4 CFRAME=red; NOTE HEIGHT=20; NOTE HEIGHT=10 JUSTIFY=center "Rho: &&coefs&n&i" JUSTIFY=center "P-Value: &&pcoefs&n&i"; 5

6 Fig 11: Output Graph from Illustration 2 Fig 11 shows the output graph generated for Illustration 2. Rho refers to the Pearson correlation coefficient; consider this as a matrix of order 3 X 3. The element [1, 2] provides the correlation plot between timepoints 1, 2, and element [2, 1] provides the corresponding correlation statistics. The graph can be interpreted in a similar way for other timepoints as well. This way, no space is wasted in presenting the symmetrical scatter plots which are produced by the option PLOTS in PROC CORR. Redundant information is not presented and space is utilized to provide additional correlation statistics. Step 4: Putting the correlation statistics and plots together PROC GREPLAY is used to define a three-by-three multi-panel template, and all the graph objects generated through GPLOT and GSLIDE are displayed on a multi-panel graph. Fig 12 shows the code for this step. 6

7 Fig 12: Code to generate graph template and multi-panel graph *Define GREPLAY template for three timepoints; PROC GREPLAY TC=sashelp.templat NOFS; TDEF h3v3 DES= "Three by Three" 1/LLX=0 LLY= 66.6 ULX=0 ULY= 100 LRX=33.3 LRY= 66.6 URX=33.3 URY=100 2/LLX=0 LLY=33.3 ULX=0 ULY=66.6 LRX=33.3 LRY= 33.3 URX=33.3 URY=66.6 3/LLX=0 LLY=0 ULX=0 ULY=33.3 LRX=33.3 LRY=0 URX=33.3 URY=33.3 4/LLX=33.3 LLY=66.6 ULX=33.3 ULY= 100 LRX=66.6 LRY= 66.6 URX=66.6 URY=100 5/LLX=33.3 LLY=33.3 ULX=33.3 ULY=66.6 LRX=66.6 LRY=33.3 URX=66.6 URY=66.6 6/LLX=33.3 LLY=0 ULX=33.3 ULY=33.3 LRX=66.6 LRY=0 URX=66.6 URY=33.3 7/LLX=66.6 LLY=66.6 ULX=66.6 ULY=100 LRX=100 LRY=66.6 URX=100 URY=100 8/LLX=66.6 LLY=33.3 ULX=66.6 ULY=66.6 LRX=100 LRY=33.3 URX=100 URY=66.6 9/LLX=66.6 LLY=0 ULX=66.6 ULY=33.3 LRX=100 LRY=0 URX=100 URY=33.3; /* assign current template */ TEMPLATE H3V3; quit; PROC GREPLAY IGOUT=work.gseg TC=sashelp.templat template=h3v3 nofs; TREPLAY 1:cslide11 2:cslide12 3:cslide13 4:gplot 5:cslide22 6:cslide23 7:gplot1 8:gplot2 9:cslide33; RUN;QUIT; CONCLUSION AND FUTURE DIRECTIONS SAS/GRAPH procedures GREPLAY, GPRINT and GSLIDE can be used to juxtapose tables/slides and graphs to provide effective communication. The GPRINT procedure can be used with PROC TABULATE with correct FORMCHAR=, DEVICE= options to produce graph objects containing tables with a solid border. The above mentioned illustrations can be easily adapted to other scenarios in both the pharmaceutical and retail industry. Illustration 2 can be extended to include tables with a solid border instead of text slides enabling the ability to present various correlation statistics like Pearson, Spearman, etc. in tables juxtaposed with correlation plots. However, the possibility of producing similar text juxtaposed with Graph objects using SAS 9.2 procedures like SGSCAT- TER need to be explored. REFERENCES: 1. SAS Institute Inc. (2004). SAS/GRAPH 9.1 Reference, Volumes 1, 2 and 3. Cary, NC: SAS Institute Inc. ACKNOWLEDGMENTS SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. indicates USA registration. Other brand and product names are registered trademarks or trademarks of their respective companies. We would like to thank our managers Amy Gillespie, Margaret Coughlin and management of MaxisIT Inc. for their kind support and cooperation. We would also like to thank Peter Hu, Biometrician, Merck & Co., Inc. for his valuable inputs. CONTACT INFORMATION Your comments and questions are valued and encouraged. Contact the author at: Author Name: Suhas R. Sanjee Author Name: Sheng Zhang Company : MaxisIT Inc. Company : Merck & Co., Inc. Address : 1199 Amboy Ave Address : 351 Sumneytown Pike City: Edison State: NJ ZIP: City: Upper Gwynedd State: PA ZIP: sanjee@maxisit.com sheng_zhang@merck.com 7