1. How to start using SAS Tina Tian

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 statistical analysis 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, 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/create SAS data libraries by assigning each a library reference name (libref) with LIBNAME statement LIBNAME libref “file-folder-location”; Eg: LIBNAME readData 'C:\temp\sas class\readData‘; Rules for naming a library reference name: 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 internal raw data in SAS system Put small amounts of raw data directly in the SAS program to create SAS data set, you must Start a DATA step and name the SAS data set being created with DATA statement Describe how to read the data fields from the raw data file with INPUT statement Use the DATALINES statement to indicate internal data The RUN statement detects the end of a step

8. Reading internal raw data in SAS system Example: DATA dog1; INPUT ID Age Gender $ Income; DATALINES; 1 10 m 2300 2 13 f 1500 3 12 f 1700 4 9 m 100 5 13 m 1000; RUN;

9. Reading external raw data files 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) The RUN statement detects the end of a step

10. Reading external raw data file into SAS system LIBNAME readData “ C:\temp\sas class”; DATA readData.dog1; INFILE “ C:\temp\sas class\dog.txt ”; INPUT ID Age Gender $ Income; RUN; The LIBNAME statement assigns a libref ‘ readData ’ to a data library. The DATA statement creates a permanent SAS data set named ‘dog1 ’. 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

11. 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 DBMS = identifier ; RUN; Type of File Extension DBMS 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: PROC IMPORT DATAFILE=‘c:\temp\sale.xls’ OUT=readData.import1; DBMS = EXCEL; RUN;

12. Reading Delimited or PC Database 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 DATA FILE = ‘filename’ OUT = data-set DBMS = identifier ; DELIMITER = ‘delimiter-character’; RUN; Examples: PROC IMPORT DATAFILE=‘c:\temp\sale.txt’ OUT=readData.import2; DBMS = DLM; DELIMITER = ‘&’; RUN;

13. 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;

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

15. 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 $.

16. Format in SAS data set Exmaple: /* Step1: Create the format for certain variables */ PROC FORMAT; VALUE $genFmt ‘m’ = 'Male' ‘f’ = 'Female'; VALUE polFmt 1=‘likes’ 2=‘dont care’ 3=‘dislikes’ 9=‘no answer’ RUN; /* Step2: Assign the variables */ DATA Mydata.dog123(replace=yes); SET Mydata.dog123; FORMAT Gender genFmt. Policy polFmt.; RUN;

17. 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 Mydata ‘C :\sas class\Format ’; OPTIONS FMTSEARCH=( Mydata.dogfmt); PROC FORMAT LIB=Myd ata.dogfmt; VALUE $genFmt m = 'Male’ f = 'Female'; RUN; Read formats OPTIONS nofmterr; OPTIONS FMTSEARCH=(Mydata.dogfmt);

18. 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.

19. Combining SAS Data Sets: Concatenating and Interleaving General form of a DATA step concatenation: DATA new SAS-data-set; SET SAS-data-set1 SAS-data-set2 …; RUN; Example: DATA mydata.dog12; SET dog1 mydata.dog2; RUN;

20. Combining SAS Data Sets: Concatenating and Interleaving General form of a DATA step interleave: DATA new-data-set; SET SAS-data-set1 SAS-data-set2 …; BY BY-variable; RUN; Sort all SAS data set first by using PROC SORT Example: PROC SORT data=dog1 OUT=dog1_sorted; BY ID; RUN; DATA mydata.dog12; SET dog1 mydata.dog2; BY ID; RUN;

21. 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: DATA new-data-set; MERGE SAS-data-set-1 SAS-data-set-2 SAS-data-set-3 …; BY by-variable(s); /* indicates the variable(s) that control which observations to match */ RUN;

22. 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 EmpIDLastName E00632Strauss E01483Lee E01996Nick E04064Waschk EmpIDFlightNum E040645105 E0632 5250 E019965501

23. Merging SAS Data Sets: A More Complex Example /* simply merge two data sets */ DATA combData.nextweek; MERGE combData.employee combData.groupsched; BY EmpID; RUN; EmpIDLastJNameFlightNum E00632Strauss5250 E01483Lee E01996Nick5501 E04064Waschk5105

24. 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: 0 indicates that the data set did not contribute to the current observation. 1 indicates that the data set did contribute to the current observation.

25. Merging SAS Data Sets: A More Complex Example /* Exclude from the data set employee who are not 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; EmpIDLastJNameFlightNum E00632Strauss5250 E01996Nick5501 E04064Waschk5105

26. 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; EmpIDLastJNameFlightNum E01483Lee

27. Different Types of Merges in SAS DATA work.three; MERGE work.one work.two; BY X; RUN; One-to-Many Merging XY 1A 2B 3C XE 1A1 1A2 2B1 3C1 3C2 XYZ 1AA1 1AA2 2BB1 3CC1 3CC2 Work.three Work.two Work.one

28. Different Types of Merges in SAS DATA work.three; MERGE work.one work.two; BY X; RUN; Many-to-Many Merging XY 1A1 1A2 2B1 2B2 XZ 1AA1 1AA2 1AA3 2BB1 2BB2 XYZ 1A1AA1 1A2AA2 1A2AA3 2B1BB1 2B2BB2 Work.three Work.two Work.one

29. Some simple analysis procedure The PRINT Procedure The CONTENTS Procedure The FREQ Procedure The SORT Procedure The MEANS Procedure The CORR Procedure The TTEST Procedure The ANOVA Procedure

30. The PRINT Procedure The PRINT procedure prints the observations in a SAS data set. General form of a simple PROC PRINT steps: PROC PRINT DATA = SAS-data-set; VAR variable(s) ; SUM variable(s) ; RUN; The VAR statement specifies which variables to print and the order The SUM statement indicates the total values of numeric variables

31. The Contents Procedure The CONTENTS procedure shows the contents of a SAS data set and prints the directory of the SAS data library General form of a simple PROC CONTENTS steps: PROC CONTENTS DATA = SAS-data-set; RUN;

32. The SORT Procedure The SORT procedure orders SAS data set observations by the values of one or more character or numeric variables. General form of a simple PROC SORT steps: PROC SORT DATA = SAS-data-set; BY variable-1 variable-n>; RUN;

33. The MEANS Procedure The MEANS procedure provides descriptive statistics for variables across all observations General form of a simple PROC MEANS steps: PROC MEANS DATA = SAS-data-set; CLASS variable(s) ; VAR variable(s) RUN;

34. The FREQ Procedure The FREQ procedure produces one-way to n-way frequency and crosstabulation (contingency) tables General form of a simple PROC FREQ steps: PROC FREQ DATA = SAS-data-set; TABLE requests ; RUN; The TABLES statement requests one-way to n-way frequency and crosstabulation tables and statistics for those tables

35. The TTEST Procedure The TTEST procedure performs t tests for one sample, two samples, and paired observations. General form of a simple PROC FREQ steps: PROC TTEST DATA = SAS-data-set H0=m; VAR variable(s); RUN; PROC TTEST DATA = SAS-data-set; VAR variable(s); CLASS variable; RUN; use H0 option to a given number in the one sample t test use CLASS statement in the two groups comparison t test

36. The ANOVA Procedure The ANOVA procedure performs one-way analysis of variance (ANOVA) for balanced data General form of a simple PROC FREQ steps: PROC ANOVA DATA = SAS-data-set; CLASS variable(s) ; MODLE dependents = effects ; RUN;

37. Some simple analysis procedure The UNIVARIATE Procedure The REG Procedure The LOGISTIC Procedure

38. The UNIVARIATE Procedure The UNIVARIATE procedure provides descriptive statistics, histograms, quartile - quartile plots (Q-Q plots) and probability plots General form of a simple PROC FREQ steps: PROC UNIVARIATE DATA = SAS-data-set; VAR variables; HISTOGRAM; QQPLOT; RUN;

39. 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 ; MODEL dependents=independents ; PLOT ; RUN;

40. An example PROC REG DATA=water; MODEL Water = Temperature Days Persons / VIF; MODEL Water = Temperature Production Days / VIF; RUN; PROC REG DATA=water; MODEL Water = Temperature Production Days; PLOT STUDENT.* PREDICTED.; /*To get studentized Residual */ PLOT STUDENT.* NPP.; /*To get Normal Cumulative Distribution*/ PLOT r.*nqq.; /*Produce normal Q-Q plot */ RUN;

41. The LOGISTIC procedure The binary or ordinal responses with continuous independent variables PROC LOGISTIC ; MODEL dependents=independents ; RUN; The binary or ordinal responses with categorical independent variables PROC LOGISTIC ; CLASS categorical variables ; MODEL dependents=independents ; RUN;

42. Example PROC LOGISTIC data=Mydata2.pain; CLASS Treatment Sex; MODEL Pain= Treatment Sex Treatment*Sex Age Duration; RUN;