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How to start using SAS

Learn how to start using SAS with this comprehensive guide covering topics such as an overview of the SAS system, reading raw data, creating SAS data sets, merging data sets, formatting data, simple regression procedure, and summary report procedures.

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How to start using SAS

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  1. How to start using SAS

  2. The topics • An overview of the SAS system • Reading raw data/ create SAS data set • Combining SAS data sets & Match merging SAS Data Sets • Formatting data • Introduce some simple regression procedure • Summary report procedures

  3. Basic Screen Navigation • Main: • Editor contains the SAS program to be submitted. • Log contains information about the processing of the SAS program, including any warning and error messages • Output contains reports generated by SAS procedures and DATA steps • Side: • Explore navigate to other objects like libraries • Results navigate your Output window

  4. SAS programs A SAS program is a sequence of steps that the user submits for execution. Data steps are typically used to create SAS data sets PROC steps are typically used to process SAS data sets (that is, generate reports and graphs, edit data, sort data and analyze data

  5. SAS Data Libraries • A SAS data library is a collection of SAS files that are recognized as a unit by SAS • A SAS data set is one type of SAS file stored in a data library • Work library is temporary library, when SAS is closed, all the datasets in the Work library are deleted; create a permanent SAS dataset via your own library.

  6. SAS Data Libraries • Identify SAS data libraries by assigning each a library reference name (libref) with LIBNAME statement LIBNAMElibref “file-folder-location”; Eg: LIBNAME readData 'C:\temp\sas class\readData‘; • Rules for naming a libref: • The name must be 8 characters or less • The name must begin with a letter or underscore • The remaining characters must be letters, numbers or underscores.

  7. Reading raw data set into SAS system • In order to create a SAS data set from a raw data file, you must • Start a DATA step and name the SAS data set being created (DATA statement) • Identify the location of the raw data file to read (INFILE statement) • Describe how to read the data fields from the raw data file (INPUT statement)

  8. Reading external raw data file into SAS system LIBNAME readData 'C:\temp\sas class\readData‘; DATAreadData.wa80; INFILE“k:\census\stf2_wa80.txt”; INPUT @10 SUMRYLVL $2. @40 COUNTY $3. @253 TABA1 9.0 @271 TABA1 9.0; RUN; • The LIBNAME statement assigns a libref ‘readData ’ to a data library. • The DATA statement creates a permanent SAS data set named ‘wa80’. • The INFILE statement points to a raw data file. • The INPUT statement - name the SAS variables - identify the variables as character or numeric ($ indicates character data) - specify the locations of the fields in the raw data - can be specified as column, formatted, list, or named input • The RUN statement detects the end of a step

  9. Reading raw data separated by spaces /* Create a SAS permanent data set named HighLow1; Read the data file temperature1.dat using listing input */ DATAreadData.HighLow1; INFILE ‘C:\sas class\readData\temperature1.dat’; INPUT City $ State $ NormalHigh NormalLow RecordHigh RecordLow; RUN; /*The PROC PRINT step creates a isting report of the readData.HighLow1 data set*/ PROC PRINT DATA = readData.highlow1; TITLE ‘High and Low Temperatures for July’; RUN; Example 1 temperature1.dat: Nome AK 55 44 88 29 Miami FL 90 75 97 65 Raleign NC 88 68 105 50

  10. Reading multiple lines of raw data per observation /*Read the data file using line pointer, slash(/) and pount-n (#n). The slash(/) indicates next line, the #n means to go to the n line for that observation. Slash(/) can be replaced by #2 here */ DATA readData.highlow2; INFILE ‘C:\sas class\readData\temperature2.dat’; INPUT City $ State $ / NormalHigh NormalLow #3 RecordHigh RecordLow; PROC PRINT DATA = readData.highlow2; TITLE ‘High and Low Temperatures for July’; RUN; Example 2 temperature2.dat: Nome AK 55 44 88 29 Miami FL 90 75 97 65 Raleign NC 88 68 105 50

  11. Reading multiple observations per line of raw data /*To read multiple observations per line of raw data,use double railing at signs (@@) at the end of INPUT statement */ DATA readData.highlow3; INFILE ‘C:\sas class\readData\temperature3.dat’; INPUT City $ State $ NormalHigh NormalLow RecordHigh RecordLow @@; PROC PRINT DATA = readData.highlow3; TITLE ‘High and Low Temperatures for July’; RUN; Example 3 temperature3.dat: Nome AK 55 44 88 29 Miami FL 90 75 97 65 Raleign NC 88 68 105 50

  12. Reading external raw data file into SAS system • Reading raw data arranged in columns INPUTFILEID $ 1-5 RECTYP $ 6-9 SUMRYLVL $ 10-11 URBARURL $ 12-13 SMSACOM $ 14-15; • Reading raw data mixed in columns INPUTFILEID $ 1-5 @10 SUMRYLVL $ 2. @253 TABA1 9.0 @271 TABA1 9.0; /* The @n is the column pointer, where n is the number of the column SAS should move to. The $w. reads standard character data, and w.d reads standard numeric data, where w is the total width and d is the number of decimal places. */

  13. Reading Delimited or PC Database Files with the IMPORT Procedure • If your data file has the proper extension, use the simplest form of the IMPORT procedure: PROC IMPORT DATA FILE = ‘filename’ OUT = data-set Type of FileExtensionDBMS Identifier Comma-delimited .csv CSV Tab-delimited .txt TAB Excel .xls EXCEL Lotus Files .wk1, .wk3, .wk4 WK1,WK3,WK4 Delimiters other than commas or tabs DLM • Examples: 1.PROC IMPORTDATAFILE=‘c:\temp\sale.csv’ OUT=readData.money; RUN; 2. PROC IMPORT DATAFILE=‘c:\temp\bands.xls’ OUT=readData.music; RUN;

  14. Reading Files with the IMPORT Procedure • If your file does not have the proper extension, or your file is of type with delimiters other than commas or tabs, then you must use the DBMS= and DELIMITER= option PROC IMPORT DATAFILE = ‘filename’ OUT = data-set DBMS = identifier; DELIMITER = ‘delimiter-character’; RUN; • Example: PROC IMPORT DATAFILE = ‘C:\sas class\readData\import2.txt’ OUT =readData.sasfile DBMS =DLM; DELIMITER = ‘&’; RUN;

  15. Format in SAS data set Standard Formats (selected): Character: $w. Date, Time and Datetime: DATEw., MMDDYYw., TIMEw.d, …… Numeric: COMMAw.d, DOLLARw.d, …… Use FORMAT statement PROC PRINT DATA=sales; VAR Name DateReturned CandyType Profit; FORMAT DateReturned DATE9. Profit DOLLAR 6.2; RUN;

  16. Format in SAS data set Create your own custom formats with two steps: Create the format using PROC FORMAT and VALUE statement. Assign the format to the variable using FORMAT statement. General form of a simple PROC FORMAT steps: PROC FORMAT; VALUE name range-1=‘formatted-text-1’ range-2=‘formatted-text-2’ ……; RUN; The name in VALUE statement is the name of the format you are creating, which can’t be longer than eight characters, must not start or end with a number. If the format is for character data, it must start with a $.

  17. Format in SAS data set Exmaple: /* Step1: Create the format for certain variables */ PROCFORMAT; VALUEgenFmt1 = 'Male' 2 = 'Female'; VALUE money low-<25000='Less than 25,000' 25000-50000='25,000 to 50,000' 50000<-high='More than 50,000'; VALUE$codeFmt 'FLTA1'-'FLTA3'='Flight Attendant' 'PILOT1'-'PILOT3'='Pilot'; RUN; /* Step2: Assign the variables */ DATA fmtData.crew1; SET fmtData.crew; FORMAT Gender genFmt. Salary money. JobCode $codeFmt.; RUN;

  18. Format in SAS data set Permanently store formats in a SAS catalog by Creating a format catalog file with LIB in PROC FORMAT statement Setting the format search options Example: LIBNAME class ‘C:\sas class\Format’; OPTIONS FMTSEARCH=(fmtData.fmtvalue); RUN; PROC FORMAT LIB=fmtData.fmtvalue; VALUE genFmt 1 = ‘Male’ 2=‘Female’; RUN;

  19. Combining SAS Data Sets: Concatenating and Interleaving • Use the SET statement in a DATA step to concatenate SAS data sets. • Use the SET and BY statements in a DATA step to interleave SAS data sets.

  20. Combining SAS Data Sets: Concatenating and Interleaving • General form of a DATA step concatenation: • DATA SAS-data-set; SET SAS-data-set1 SAS-data-set2 …; RUN; • Example: DATA stack.allEmp; SET stack.emp1 stack.emp2 stack.emp3; RUN;

  21. Combining SAS Data Sets: Concatenating and Interleaving • General form of a DATA step interleave: • DATASAS-data-set; SETSAS-data-set1 SAS-data-set2 …; BYBY-variable; RUN; • Sort all SAS data set first by using PROC SORT • Example: PROC SORT data=stack.emp2 OUT=stack.emp2_sorted; BY Salary; RUN; DATA stack.allEmp; SET stack.emp1 stack.emp2 stack.emp3; BY salary; RUN;

  22. Match-Merging SAS Data Sets • One-to-one match merge One-to-many match merge Many-to-many match merge • The SAS statements for all three types of match merge are identical in the following form: DATAnew-data-set; MERGEdata-set-1 data-set-2 data-set-3 …; BYby-variable(s); /* indicates the variable(s) that control which observations to match */ RUN;

  23. Merging SAS Data Sets: A More Complex Example /*To match-merge the data sets by common variables - EmpID, the data sets must be ordered by EmpID*/ PROC SORT data=combData.Groupsched; BY EmpID; RUN; • Example: Merge two data sets acquire the names of the group team that is scheduled to fly next week. combData.employee combData.groupsched

  24. Merging SAS Data Sets: A More Complex Example /* simply merge two data sets */ DATA combData.nextweek; MERGE combData.employee combData.groupsched; BY EmpID; RUN;

  25. Merging SAS Data Sets: A More Complex Example • Eliminating Nonmatches Use the IN= data set option to determine which dataset(s) contributed to the current observation. • General form of the IN=data set option: SAS-data-set (IN=variable) • Variable is a temporary numeric variable that has two possible values: • 0indicates that the data set did not contribute to the current observation. • 1 indicates that the data set did contribute to the current observation.

  26. Merging SAS Data Sets: A More Complex Example /*Exclude from the data set employee who are scheduled to fly next week. */ LIBNAME combData “K:\sas class\merge”; DATA combData.nextweek; MERGE combData.employee combData.groupsched (in=InSched); BY EmpID; IF InSched=1; True RUN;

  27. Merging SAS Data Sets: A More Complex Example /* Find employees who are not in the flight scheduled group. */ LIBNAME combData “K:\sas class\merge”; DATA combData .nextweek; MERGE combData .employee (in=InEmp) combData.groupsched (in=InSched); BY EmpID; IF InEmp=1; True IF InSched=0; False RUN;

  28. One-to-Many Merging Different Types of Merges in SAS DATA work.three; MERGE work.one work.two; BY X; RUN; Work.two Work.one Work.three

  29. Many-to-Many Merging Different Types of Merges in SAS DATA work.three; MERGE work.one work.two; BY X; RUN; Work.two Work.one Work.three

  30. Some simple regression analysis procedure • The REG Procedure • The LOGISTIC Procedure

  31. The REG procedure • The REG procedure is one of many regression procedures in the SAS System. • The REG procedure allows several MODEL statements and gives additional regression diagnostics, especially for detection of collinearity. It also creates plots of model summary statistics and regression diagnostics. • PROC REG <options>; MODEL dependents=independents </options>; PLOT <yvariable*xvariable>; RUN;

  32. An example • PROCREGDATA=water; MODEL Water = Temperature Days Persons / VIF; MODEL Water = Temperature Production Days / VIF; RUN; • PROCREG DATA=water; MODEL Water = Temperature Production Days; PLOT STUDENT.* PREDICTED.; PLOT STUDENT.* NPP.; PLOTNPP.*r.; PLOTr.*NQQ.; RUN;

  33. The LOGISTIC procedure • The binary or ordinal responses with continuous independent variables PROC LOGISTIC< options > ; MODEL dependents=independents < / options > ; RUN; • The binary or ordinal responses with categorical independent variables PROC LOGISTIC< options > ; CLASS categorical variables < / option > ; MODELdependents=independents < / options > ; RUN;

  34. Example PROC LOGISTIC data=Neuralgia; CLASS Treatment Sex; MODELPain= Treatment Sex Treatment*Sex Age Duration; RUN;

  35. Overview Summary Report Procedures PROC FREQ: produce frequency counts PROC TABULATE: produce one- and two-dimensional tabular reports PROC REPORT: produce flexible detail and summary reports

  36. The FREQ Procedure The FREQ procedure display frequency counts of the data values in a SAS data set. General form of a simple PROC FREQ steps: PROC FREQ DATA = SAS-data-set; TABLESAS-variables</options>; RUN;

  37. The FREQ Procedure Example: PROCFREQ DATA = class.crew ; FORMAT JobCode $codefmt. Salary money.; TABLE JobCode*Salary /NOCOL NOROW OUT =freqTable; RUN;

  38. The TABULATE Procedure PROC TABULATE displays descriptive statistics in tabular format. General form of a simple PROC TABULATE steps: PROC TABULATE DATA=SAS-data-set; CLASSclass-variables; VARanalysis-variables; TABLErow-expression, column-expression</options>; RUN;

  39. The TABULATE Procedure Example: TITLE 'Average Salary for Cary and Frankfurt'; PROCTABULATEDATA= class.crew FORMAT=dollar12.; WHERE Location IN ('Cary','Frankfurt'); CLASS Location JobCode; VAR Salary; TABLE JobCode, Location*Salary*mean; RUN;

  40. The REPORT procedure REPORT procedure combines features of the PRINT, MEANS, and TABULATE procedures. It enables you to create listing reports create summary reports enhance reports request separate subtotals and grand totals

  41. The REPORT procedure Example PROCREPORTDATA =class.crew nowd HEADLINE HEADSKIP; COLUMN JobCode Location Salary; DEFINE JobCode / GROUP WIDTH= 8 'Job Code'; DEFINE Location / GROUP 'Home Base'; DEFINE Salary / FORMAT=dollar10. 'Average Salary‘ MEAN ; RBREAK AFTER / SUMMARIZE DOL; RUN;

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