How to Go From SAS Data Sets to DATA NULL or WordPerfect Tables Anne Horney, Cooperative Studies Program Coordinating Center, Perry Point, Maryland ABSTRACT Clinical trials data reports often contain many tables produced on a recurring basis, and a way is needed to move information from SAS procedures into publication quality tables without spending hours transferring and checking numbers. Combining output values from several procedures into one table or page of a report is often necessary. The data values/information can be calculated using several methods such as PROC FREQ, PROC MEANS, and DATA steps. The table can be created using PUT statements or the data can be written to a delimited ASCII file that can be merged into word processing or spreadsheet packages. An example of a report table created by both DATA _NULL_ and WordPerfect will be shown. INTRODUCTION The goal is to produce a table that describes a continuous variable (Age) and two categorical variables (Gender and Marital Status) by treatment group. As is so often the case in SAS programming, there is more than one way to accomplish the task. SAS procedures and DATA step programming will be used to show some ways to meet the goal. Statistics for the continuous variable will be n, mean, standard deviation and the probability of no difference between treatment groups; for the discrete variables statistics will be n, percent-of-group, and probability of no difference between groups. Our sample data set form1 contains five variables: Id Subject identifier Treatmnt Treatment A or B Age Subject's age in years Gender 1=male, 2=female MarStat 1=never married, 2=married, 3=divorced/widowed The 51 observations have been sorted by treatment group; none of the data are missing. Assume the formats gender. and marital. exist. STEP ONE - CALCULATING THE STATISTICS N, MEAN, AND STANDARD DEVIATION USING PROC MEANS One method of calculating statistics such as means and standard deviations is to use the procedure PROC MEANS, which can create an output data set containing the calculated values. The output data set is named in the OUTPUT statement; the desired statistics are requested and named. When the CLASS statement is used, the data set contains statistics for each value of the class variable (here, treatmnt) and for the total sample. The data step AGEA changes the value of treatmnt for the total sample from ' ' (missing) to 'C' so that the data can be sorted to put the total last. proc means data=form1; class treatmnt; var age; output out=age n=n_age mean=m_age std=s_age; data agea; set age; if treatmnt=' ' then treatmnt='c'; keep treatmnt n_age m_age s_age; proc sort; by treatmnt; N AND PERCENT USING ARRAYS IN A DATA STEP The number occurrences of each category of a discrete variable and percentages are calculated in a DATA step. An array is defined for each categorical variable of interest. The array GEN will be used to sum the occurrences of 1(male) and 2(female) for each treatment group and overall; likewise, MARITAL will hold the marital status counts. For each two-dimensional array the rows are the categories and the columns are the treatment groups. The percentages will be calculated later in the DATA _NULL_ step. data counts(keep=gen1-gen9 mar1-mar12); set form1 end=eof; *columns: Treament A, B, total; *Rows: Male, Female, Total; array gen{3,3} gen1-gen9; *Rows: Nvr Married,Married,Divorced,total; array marital{4,3} mar1-mar12; retain gen1-gen9 mar1-mar12 0; if treatmnt='a' then trt=1; if treatmnt='b' then trt=2; if gender in (1,2) then do; gen{gender,trt}+1; gen{gender,3}+1; *row total; gen{3,trt}+1; *column total; gen{3,3}+1; *overall total; if 1 le marstat le 3 then do; marital{marstat,trt}+1; marital{marstat,3}+1; *row total; marital{4,trt}+1; *column tot; marital{4,3}+1; *overall tot; if eof then output;
T-TEST P-VALUE USING ANOVA PROCEDURE Since the TTEST procedure does not have an OUTPUT option, the ANOVA procedure, which calculates the equivalent probability value is used. proc anova data=form1 outstat=p_age; class treatmnt; model age=treatmnt; CHI-SQUARE PROBABILITY USING PROC FREQ Counts and percentages, as well as chi-square probabilities, for discrete variables can be obtained by use of the procedure FREQ along with the procedure s two types of output statements. For this example only the chi-square probabilities are be used. Proc freq data=form1; table gender*treatmnt /chisq; output out=cgender(keep=p_pchi) chisq; proc freq data=form1; table marstat*treatmnt /chisq; output out=cmarital(keep=p_pchi) chisq; STEP TWO - PRODUCING THE TABLE METHOD ONE: DATA _NULL_ AND PUT The table is produced in a DATA _NULL_ step by bring the pieces together and using the PUT statement to write out the data in tabular form. data _null_; set agea(in=ina ) counts(in=inc); array gen{3,3} gen1-gen9; array marital{4,3} mar1-mar12; retain col 0; file print header=h1; *Age*; if ina then do; col+17; if treatmnt='a' then put / @1 'Age (years)' @; put @col n_age 2. +2 m_age 4.1 +2 s_age 4.1 @; if treatmnt='c' then do; set p_age (where=(_type_='anova')); put @71 prob 5.3; if inc then do; Demographic Information by Treatment Group Treatment Group A B Total Demographic Information N Mean S.D. N Mean S.D. N Mean S.D. probability Age (years) 25 34.7 9.1 26 33.9 8.5 51 34.3 8.7 0.736 N % N % N % probability Gender Male 14 56.0 14 53.8 28 54.9 0.877 Female 11 44.0 12 46.2 23 45.1 Marital Status Single 7 28.0 5 19.2 12 23.5 0.558 Married 10 40.0 9 34.6 19 37.3 Divorced 8 32.0 12 46.2 20 39.2 Figure 1
*Gender*; put /// @20 'N %' @37 'N %' @54 'N %' @68 'probability' / @19 ' ' @36 ' ' @53 ' ' @68 ' '; / @1 'Gender'; do row=1 to 2; put @3 row :gender. @; col=2; col=col+17; if gen{3,rx} gt 0 then pc=gen{row,rx}/gen{3,rx} * 100; put @col gen{row,rx} 2. + 3 pc 5.1 @; set cgender; put @71 p_pchi 5.3; *Marital Status*; put // @1 'Marital Status'; do row=1 to 3; put @3 row :marital. @; col=2; col=col+17; if marital{4,rx} gt 0 then pc=marital{row,rx}/marital{4,rx} * 100; put @col marital{row,rx} 2. +3 pc 5.1 @; set cmarital; put @71 p_pchi 5.3; return; h1: title 'Demographic Information by' 'Treatment Group'; put // @33 'Treatment Group' // @23 'A' @40 'B' @56 'Total' / @1 'Demographic' / @1 'Information' @17 ' N Mean S.D.' @34 ' N Mean S.D.' @51 ' N Mean S.D.' @68 'probability' / @1 ' ' @17 ' ' @34 ' ' @51 ' ' @68 ' '; METHOD TWO: WORDPERFECT The Data And Safety Monitoring Board Reports produced by the Cooperative Studies Program Coordinating Center include many pages of tables. The reports are prepared semiannually for the duration of the study. A way was needed to move information from SAS outputs into publication quality tables without spending hours transferring and checking numbers and repeating the process again in six months. We used SAS and WordPerfect to produce the necessary report tables with a minimum of manual intervention. Examples of report tables and of the data and WordPerfect macros that produced them will be displayed. INFORMATION The first step is to determine what information is to appear in the table. Design the table in WordPerfect as a merge form file (see Figure 2). Decide on title lines, contents and placement of columns and rows, and labeling. The form file will be a combination of text and merge codes. The text entries will remain constant. Put the merge code FIELD in each location where text and/or numeric data will be inserted from the merge data file. These fields are consecutively numbered. Information can be merged into titles, and headers and footers, as well as table cells. The merge data file is an ASCII file created in SAS. The macro RENUMBER can be used to number the fields. Put the tilde symbol "~" in the document where you want a merge field code. The macro will insert the field codes numbered appropriately. It can also be used to renumber the fields if the table is changed. ASCII DELIMITED TEXT FILE The information that will be merged into the table must be put into an ASCII delimited text file, the data file. Entries must be placed in the file in the same order as the field numbers in the form file. This is done with SAS PUT statements. The delimiters can be any characters you choose. (WordPerfect uses a comma as the default field delimiter and [CR][LF] as the default record delimiter.) If you plan to use the merge command from the menu or merge bar there must be a record delimiter after the last record. If you plan to merge the table using a WordPerfect macro, omit the record delimiter after the last record. For both methods, separate multiple records with delimiters. The example is for use with a macro. data _null_; set agea(in=ina ) counts(in=inc); array gen{3,3} gen1-gen9; array marital{4,3} mar1-mar12; file 'c:\nesug01\table1.dat'; *Age*; if ina then do; put n_age :2. '*' m_age :4.1 '*,' s_age :4.1 '*'@;
if treatmnt='c' then do; set p_age(where=(_type_='anova')); put prob :5.3 '*'; if inc then do; *Gender*; do row=1 to 2; if gen{3,rx} gt 0 then pc=gen{row,rx}/gen{3,rx} * 100; put gen{row,rx} :2. '*' pc 5.1 '*' @; set cgender; put p_pchi :5.3 '*'; else put; *Marital Status*; do row=1 to 3; if marital{4,rx} gt 0 then pc=marital{row,rx}/marital{4,rx} * 100; put marital{row,rx} :2. '*' pc 5.1 '*' @; set cmarital; put p_pchi :5.3 '*'; else put; Sample data file: 25 *34.7 *9.1 *26 *33.9 *8.5 *51 *34.3 *8.7 *0.736 * 14 *56.0 *14 *53.8 *28 *54.9 *0.877 * 11 *44.0 *12 *46.2 *23 *45.1 * 7 *28.0 *5 *19.2 *12 *23.5 *0.558 * 10 *40.0 *9 *34.6 *19 *37.3 * 8 *32.0 *12 *46.2 *20 *39.2 * WORDPERFECT TABLE The study table (see Figure 3), containing the desired information in the desired format, is achieved by merging the ASCII data file into the WordPerfect form file using the WordPerfect Merge command. Whenever the study data change, a new data file can be prepared and merged into the form file... yielding a relatively quick and painless revised study table. TABLE MACRO WordPerfect macros are used to automate the merging process. For each table a macro is written containing all the statements required to produce the finished version of the table from a form file and a data file. The WordPerfect macro merges the form with the data and saves the resulting table as a WordPerfect document. Demographic Information by Treatment Group Treatment Group Demographic Information A B Total N Mean S.D. N Mean S.D. N Mean S.D. Probability Age(years) FIELD(1) FIELD(2) FIELD(3) FIELD(4) FIELD(5) FIELD(6) FIELD(7) FIELD(8) FIELD(9) FIELD(10) N % N % N % Gender Male FIELD(11) FIELD(12) FIELD(13) FIELD(14) FIELD(15) FIELD(16) FIELD(17) Female FIELD(18) FIELD(19) FIELD(20) FIELD(21) FIELD(22) FIELD(23) Marital Status Single FIELD(24) FIELD(25) FIELD(26) FIELD(27) FIELD(28) FIELD(29) FIELD(30) Married FIELD(31) FIELD(32) FIELD(33) FIELD(34) FIELD(35) FIELD(36) Divorced FIELD(37) FIELD(38) FIELD(39) FIELD(40) FIELD(41) FIELD(42) Figure 2. WordPerfect Form File
REPORT MACRO Carrying this a giant step forward, a WordPerfect Report macro, has been written to produce the final report. First the Report macro runs each individual table macro (the command is NEST) and creates a WordPerfect file for each table. Next the Report macro inserts each table in the correct order into a single large document. Also, the macro can issue additional WordPerfect commands, such as headers, footers, and page numbers, to bring the final document into its desired form. CONCLUSION Using DATA step arrays and/or output data sets from SAS procedures will require some extra programming steps. The time is well spent, though, when you compare the programming time to the alternative of hand-transcribing, checking, checking again, and verifying that the correct numbers from the appropriate SAS output listings have been put in the correct destination slots. We prepare the study report by running SAS programs to prepare the data files and by playing one WordPerfect macro. Thus we have eliminated time-consuming and error-prone repetitive transcribing and checking. ACKNOWLEDGMENTS The author wishes to thank Gail Kirk for her contributions to this paper. SAS is a registered trademark or trademark of SAS Institute Inc.. WordPerfect is a registered trademark of Corel Corporation Limited, in the USA and other countries. indicates USA registration. CONTACT INFORMATION Anne Horney CSPCC (151E) VA Medical Center P. O. Box 1010 Perry Point, MD 21902 410-642-2411 ext. 5298 rebecca.horney@med.va.gov The WordPerfect macros were written for WordPerfect version 7. Some changes to the macros may be required for other versions. The SAS programs were written for Version 6.12, they will also work with version 8. Demographic Information by Treatment Group Treatment Group Demographic Information A B Total N Mean S.D. N Mean S.D. N Mean S.D. Probability Age(years) 25 34.7 9.1 26 33.9 8.5 51 34.3 8.7 0.736 N % N % N % Gender Male 14 56.0 14 53.8 28 54.9 0.877 Female 11 44.0 12 46.2 23 45.1 Marital Status Single 7 28.0 5 19.2 12 23.5 0.558 Married 10 40.0 9 34.6 19 37.3 Divorced 8 32.0 12 46.2 20 39.2 Figure 3. WordPerfect Table
Renumber Macro //Description: RENUMBER renumber all fields PosDocVeryTop SearchString ("[MRG: FIELD]") ReplaceString ("~") ReplaceForward (Extended!) PosDocVeryTop () ForNext(LP;1;3;1) ForNext(num; 0; 9; 1) PosDocTop ReplaceConfirm(No!) SearchString("~"+num) ReplaceString("~") ReplaceForward(Extended!) ENDFOR ENDFOR PosDocVeryTop () ASSIGN(NUM; "0") LABEL (Begin@) ASSIGN(NUM; NUM+1) OnNotFound(labelb) SearchString ("~") SearchNext (Extended!) SelectMode (Off!) MergeCode (Field!; NUM) GO(Begin@) LABEL(labelb) PosDocVeryTop SearchString ("~") ReplaceString ("") ReplaceForward (Extended!) beep PosDocVeryTop Table Macro //table1 Application (A1; "WordPerfect"; Default; "US") //names of the merge form file, merge data file, //resulting merged document CONSTANT( vform: = "c:\nesug01\table1.frm"; vdata: = "c:\nesug01\table1.dat"; vtable: = "c:\nesug01\table1.wpd") //Data file ImportSetFileName (vdata) ImportSetSource (ASCII!) ImportSetDestination (MergeData!) //Field Delimiter - macro uses * as the field delimiter // ----- can be changed ImportSetAsciiFieldDelimiter ("*") //Record Delimiter - macro does not use a record //delimiter ----- can be changed ImportSetAsciiRecordDelimiter ("") //Hard returns are removed from the data file before //merging into the form file //if you don't want hard returns deleted from the ascii //file - delete the text between the quotes in //(StripChars: "[SRt][HRt]") ImportSetAsciiStrip (StripChars: "[SRt][HRt]") //text strings are surrounded by "" // ----- can be changed ImportSetAsciiEncap (EncapsulationChar: """") //convert data file to a merge file and copy to //clipboard ViewDraft () ImportDoImport () PosDocTop () SelectDocBottom () EditCopy () Close (No!) //do the merge MergeSelect (All!) //form file name, data file source, location of merged //document MergeRun (FormFile!; vform;datafiletype: Clipboard!; OutputFileType: ToNewDoc!) //name of the document containing the merged table FileSave(vTable;WordPerfect_60!) Close
Report Macro Application (A1; "WordPerfect"; Default; "US") PERSISTALL DEFAULTUNITS(Inches!) VARERRCHK(OFF!) DISPLAY(Off!) //play macro to create table Table1 NEST("C:\nesug01\Table1") //play macro to create table Table2 NEST("C:\nesug01\Table2") //play macro to create table Table3 NEST("C:\nesug01\Table3") //play macro to create table Table4 NEST("C:\nesug01\Table4") //Assemble report //insert cover sheet FileInsert("C:\nesug01\DSMB.WPD"; //insert Table of Contents FileInsert("C:\nesug01\DSMBCONT.WPD") //discontinue the header that is used in the Table of // Contents HeaderA(Off!) //put page numbers on bottom of pages, starting with page 1 PageNumberPosition (Position: BottomCenter!; Default: DontUseDefaultValues!) PageNumberMethod(Numbers!) PageNumber(1) //insert the table Table1 -file created by macro // Table1 FileInsert("C:\nesug01\Table1.WPD" ; //insert the table Table2 - file created by macro // Table2 FileInsert("C:\nesug01\ Table2.WPD"; //insert the table Table3 - file created by macro // Table3 FileInsert("C:\nesug01\Table3.WPD"; //insert the table Table4 - file created by macro // Table4 FileInsert("C:\nesug01\Table4.WPD";