1. USING SAS PROCEDURES SAS System Options OPTIONS Statement
SAS System options are parameters you can change that affect the SAS System – how it works, what the output looks like, error handling, and so forth.
You can set system options in the SAS System Options window, in an OPTIONS statement, or in a couple of other ways. In this class we will focus on the OPTIONS statement.
OPTIONS Statement
An OPTIONS statement is submitted as part of a SAS program and affects all steps that follow it.
This chapter is about procedures, but first let’s talk about SAS System options. The settings of these options can affect the appearance of the output from procedures.

2. OPTIONS Statement
The OPTIONS statement is one of the special SAS statements that do not belong to either a PROC or a DATA step.
It can appear anywhere in a program, but often the very first line in a program is an OPTIONS statement. That way you can easily see what options are in effect.
Any subsequent OPTIONS statements in a program override previous ones.

3. OPTIONS Statement Commonly Used Options
CENTER | NOCENTER This option works as a switch. CENTER centers output on a page, while NOCENTER left justifies output.
DATE | NODATE This option is also a switch. DATE places today’s date at the top of each page of output.
NUMBER | NONUMBER This switch controls whether a page number appears on each page of output.
LINESIZE = n Use LINESIZE to control the maximum length of output lines. Takes values from 64 to 256. A linesize of 98 or less tends to work well for SOCI6200 assignments.
PAGESIZE = n Use PAGESIZE to control the maximum number of lines per page of output. Takes values from 15 to A pagesize of 55 or less tends to work well for SOCI6200 assignments.
PAGENO = n Starts numbering pages with n.
FORMDLIM=’-‘ Asks SAS to write a line of dashes (--) where normally it would go to a new page, thus possibly conserving paper.

4. The PROC Step SAS procedures are computer programs that:
read SAS data sets
compute statistics
write results
create SAS data sets
We will examine the following procedures:
SORT Sorts observations by one or more variables.
CONTENTS Provides information about a SAS data set.
PRINT Prints the observations in a SAS data set using some or all of the variables.
FREQ Produces one-way to n-way frequency and crosstabulation tables as well as many measures of association.
UNIVARIATE Provides data summarization tools and information on the distribution of numeric variables.
MEANS Produces descriptive statistics for numeric variables.

5. Using SAS Procedures
Using a procedure is like filling out a form. Someone else designed the form, and all you have to do is fill in the blanks and choose from a list of options.
Most procedures write results to the Output window or to a listing file, depending on how you are running SAS.
You can customize the appearance of the output using the system options described above.
Many procedures can also write results to an output SAS data set using an OUTPUT statement or an OUT= option.
Several other statements can be used with almost every procedure. These optional statements include BY, WHERE, TITLE, FOOTNOTE, LABEL, and FORMAT.
All procedures can use the Output Delivery System (ODS) to produce results that are more attractive than the default.

6. Using SAS Procedures PROC Statement
Each PROC step begins with a PROC statement.
A PROC statement consists of the word PROC followed by the name of the procedure you want to run, followed by any procedure options you want to set for this run.
The procedure options should almost always include DATA=<data set name> to specify the data set that you want to analyze.
This example asks PROC PRINT to print the weight_club data set double-spaced.
PROC PRINT DATA=weight_club DOUBLE;

7. BY Statement BY Statement
A BY statement tells the procedure to perform a separate analysis for each combination of values of the BY variables rather than treating all observations as one group.
All procedures except PROC SORT assume that your data are already sorted by the variables in your BY statement. If they are not, use PROC SORT to do so.

8. BY Statement
This example sorts the weight_club data set by team and then computes the average weight loss for each team.

9. WHERE Statement WHERE Statement
The WHERE statement tells the procedure to use a subset of the data. The basic form of a WHERE statement is
Only observations satisfying the condition will be used by the PROC. The left side of the condition must be a variable name, and the right side of the condition can be a variable name, a constant, or a mathematical equation.

10. WHERE Statement: operators
Here are the most frequently used operators:

11. WHERE Statement
For example, this PROC step prints only the members of the yellow team.

12. TITLE Statement TITLE Statement
Use TITLE statements to place descriptive information at the top of every page of output. The basic form of a TITLE statement is TITLE followed by the text of the title in quotes.
You can specify up to ten titles by adding numbers to the keyword TITLE. Keyword TITLE is the same as TITLE1.
The basic form of a TITLE statement is TITLEn followed by the text of the title in quotes.
You can use either single or double quotes as long as they are the same on either end of the text. If you want to put an apostrophe in a title, use double quotes.

13. TITLE Statement
TITLE statements can appear anywhere in a program, not just in a PROC step, but it often makes sense to put them in PROC steps since they affect procedure output.
The maximum length of a title is 256 characters or the current linesize, whichever is less.
Once you specify a title for a line, it is used for all subsequent output until you cancel the title with a null statement or define another title for that line. A null statement for TITLE2 would be the following:
The flowing cancels all existing titles.

14. FOOTNOTE Statement FOOTNOTE statement
The FOOTNOTE statement works exactly the same way as the TITLE statement. However, footnotes print at the bottom of the page.
FOOTNOTE ‘your comments’;
FOOTNOTE1 ‘your comments’;
FOOTNOTE2 ‘your comments’;
FOOTNOTE;

15. LABEL Statement LABEL Statement
By default, SAS uses variable names to label your output, but with the LABEL statement you can create more descriptive labels, up to 256 characters long, for each variable.
When a LABEL statement is used in a DATA step, the labels are permanently attached to the variables. When used in a PROC step, the labels stay in effect only for the duration of that step.
Labels containing special characters such as “ or ; must be enclosed in single quotes.
Labels containing single quotes must be enclosed in double quotes. Otherwise, labels can be enclosed in either single or double quotes.

16. FORMAT Statement FORMAT Statement
Formats can be used to change the appearance of printed values – how many decimal places to print, to show a $ when a variable contains amounts of money, etc. Base SAS includes many formats for numeric, character, and date values.
You use a FORMAT statement to associate formats with particular variables. This statement is mentioned here because it is commonly used in PROC steps. However, we will save a detailed discussion of formats for a later class.

17. The Output Delivery System (ODS)
The Output Delivery System (ODS) can be used to make your procedure output more visually appealing and more portable to other software packages than is traditional SAS output. You can make HTML files to display on the web, RTF files to import into Microsoft Word, or PDF files to read with Acrobat Reader. All procedures support ODS.
We will save a detailed discussion of this topic for later in this module.

18. An example program
Here is a simple program that uses many of the statements described above, followed by the output.

19. Output of the example program

20. The SORT Procedure
The SORT procedure sorts observations in a SAS data set by one or more variables, storing the sorted observations in a new SAS data set or replacing the original data set.
Windows and UNIX use the ASCII collating sequence.
Sorting character variables:
Sorting numeric variables
Features include:
multiple sort fields
ascending or descending order

21. The SORT Procedure Basic form of the PROC SORT statement:
Statement used with PROC SORT:

22. An example program PROC SORT DATA=SOCI6200.sales OUT=sales ;
BY dept DESCENDING clerk ;
RUN;
PROC PRINT DATA=sales NOOBS ;
TITLE 'Sorting a SAS Data Set' ;

23. BY Group Processing
The BY statement can be used with procedures to perform subgroup processing.
The PROC will be executed separately for each of the subsets of observations defined by the values of the BY variables.
Syntax:
The data set must be sorted as specified in the BY variable list.

24. An example program and output
PROC SORT DATA=SOCI6200.sales OUT=sales ;
BY dept ;
RUN;
PROC MEANS DATA=sales ;
TITLE 'PROC MEANS by DEPT' ;

25. The CONTENTS Procedure
PROC CONTENTS prints the descriptor information from a SAS data set.
It lists data set attributes followed by all variables and their attributes in alphabetical order. Variable attributes displayed include type, length, label (if present), and format (if present).
PROC CONTENTS is especially useful for documenting a permanent data set since it displays the data set creation date and date of last modification.
Basic form of the PROC statement:

26. An example program and output
PROC CONTENTS DATA=weight_club;
RUN;

27. The PRINT Procedure
The PRINT procedure lists the observations in a SAS data set, using all or some of the variables.
Features include:
Automatic formatting
Columns labeled with variable names or labels
Special handling of section and page breaks
If requested, accumulation and printing of subtotals and totals
Special BY/ID formatting
Basic form of the PROC statement:

28. The PRINT Procedure Selected procedure statement options:
DOUBLE Double-spaces the output.
LABEL Uses variable labels as column headings. If this option is not specified, variable names are used as column headings.
N Prints the number of observations at the end of the printed output.
NOOBS Suppresses the observation number column in the printed output.
Special statements supported by PROC PRINT:
VAR variable_list ;
ID variable_list ;
PAGEBY name_of_by_variable ;
SUM variable_list ;
SUMBY name_of_by_variable ;

29. The PRINT Procedure VAR Statement
The VAR statement selects the variables to appear in the report and determines their order.
The basic form of the VAR statement is
VAR variable-list;
variable-list can be one of the following
VAR x1 x2 x3;
Range of variables in positional order: VAR name--age ;
Numeric suffix ranges: VAR x1-x3;
Only numeric variables: VAR _numeric_ ;
Only character variables: VAR _character_ ;
All variables starting with the letter A : VAR A: ;
All variables starting with the letters AB: VAR AB: ;

30. The PRINT Procedure ID Statement
If an ID statement is included in a PROC PRINT step, observations in the listing are identified by the value of the ID variable(s) rather than by observation number.
The basic form of the ID statement is
ID variable-list;
The variables in the ID statement list appear before any variables in the VAR statement list.
Even without an ID statement, the NOOBS option of the PROC PRINT statement can be used to turn off observation numbers.

31. The PRINT Procedure Sample results without an ID statement
PROC PRINT DATA=weight_club;
VAR name team loss;
RUN;

32. The PRINT Procedure
Sample results with an ID statement

33. The PRINT Procedure PAGEBY Statement
The PAGEBY statement can be used to identify a variable appearing in the BY statement in the same PROC PRINT step. If the value of this BY variable changes, or if the value of any BY variable that precedes it in the BY statement changes, PROC PRINT begins printing a new page.
The general form of the PAGEBY statement is
PAGEBY name_of_by_variable;
SUM Statement
The SUM statement identifies any numeric variables to total in the report.
The general form of the SUM statement is
SUM variable(s);

34. The PRINT Procedure SUMBY Statement SUMBY name_of_by_variable;
The SUMBY statement can be used with the SUM statement to limit the number of sums that appear in the report. The SUMBY statement can be used to identify a variable appearing in the BY statement in the same PROC PRINT step. If the value of this BY variable changes, or if the value of any BY variable that precedes it in the BY statement changes, PROC PRINT prints the sums of all variables listed in the SUM statement.
The general form of the SUMBY statement is
SUMBY name_of_by_variable;

35. PROC PRINT Examples PROC PRINT DATA=weight_club N NOOBS DOUBLE;
SUM loss;
TITLE 'Listing of the Weight_Club Data Set';
TITLE2 'Using the N, NOOBS, and DOUBLE Options';
TITLE3 'Also, Using a SUM Statement But No VAR Statement';
RUN;
Sum of Loss
# of obs

36. Print certain # of observations
PROC PRINT DATA=SOCI6200.sales(OBS=20);
VAR _CHARACTER_;
TITLE1 'Listing of the First 20 Observations of the SALES Data Set';
TITLE2 'Only Character Variables';
RUN;

37. PROC PRINT example PROC SORT DATA=SOCI6200.sales OUT=sales;
BY dept clerk;
RUN;
PROC PRINT DATA=sales(OBS=25) LABEL;
WHERE price > 60;
VAR price cost;
SUM price;
SUMBY dept;
LABEL cost='Cost of Item‘ price='Price of Item';
TITLE1 'Partial Listing of Sales Data Set';
TITLE2 'Using Selected Options and Statements';

38. The FREQ Procedure Basic form of the PROC FREQ statement:
The FREQ procedure produces one-way to n-way frequency and crosstabulation tables.
distributions of variable values (frequency counts)
tests for proportions for one-way tables
combined frequencies for two or more variables
weighted frequencies
measures of association and tests (chi-square and exact) for n-way tables
ability to output frequencies to a SAS data set
stratified analysis, within and across strata
Basic form of the PROC FREQ statement:
PROC FREQ DATA = data_set_name options ;

39. The FREQ Procedure The TABLES statement: one-way: tables variable ;
TABLES table_requests / options ;
one-way: tables variable ;
two-way: tables var_1 * var_2 ;
three-way: tables var_1 * var_2 * var_3 ;
For two- to n-way tables, the last variable is the column variable and the next-to-last variable is the row variable. Other variables can be called stratum variables.
Any # of requests can be given in one TABLES statement.
Any # of TABLES statements can be used in one PROC FREQ step.
By default, missing levels of each variable are excluded from the table, but the total frequency of missing observations is printed below each table.

40. The FREQ Procedure: some options
NOFREQ suppresses frequencies NOCUM suppresses cumulative frequencies and percentages NOPERCENT suppresses percentages NOROW suppresses row percentages NOCOL suppresses column percentages MISSPRINT prints missing value frequencies for two- to n-way tables; MISSING interprets missing values as non-missing and includes them in calculations of % and other statistics LIST presents two- to n-way tables in list format rather than as crosst tables
OUT= names an output data set to contain
variable values and frequency counts
OUTPCT adds percentages to OUT= data set
SPARSE lists all possible combinations of the
variable values for an n-way table even if a
combination does not occur in the data;
only has an effect with the LIST or OUT=.
ALL requests tests and measures of association
produced by CHISQ, MEASURES, and
CMH
CHISQ requests chi-square tests and measures
of association based on chi-square
MEASURES requests measures of association
CMH computes Cochran-Mantel-Haenzel
statistics

41. The FREQ Procedure: examples
Basic example
Example suppressing percents
Missing data example
PROC FREQ DATA=sales;
TABLES dept clerk dept*clerk;
RUN;
PROC FREQ DATA=sales;
TABLES dept*clerk / NOROW NOCOL NOPERCENT;
TITLE1 "Table with Percents Suppressed";
RUN;
PROC FREQ DATA=clin ;
TABLES evdnk*visit ;
TABLES evdnk*visit / MISSPRINT ;
TABLES evdnk*visit / MISSING ;
TITLE1 "Missing Data Example" ;
RUN;

42. The FREQ Procedure: examples
Example using the ALL option
Using WEIGHT statement
WEIGHT var-name-of-counts;
PROC FREQ DATA=sales2 ;
TABLES sex*clerk / ALL ;
TITLE 'Example with the ALL Option';
RUN;

43. The UNIVARIATE Procedure
The UNIVARIATE procedure provides data summarization tools, high-resolution graphics displays, and information on the distribution of numeric variables.
Descriptive statistics
Details on extreme values and extreme observations
Median, mode, range, and quantiles
Tests for location and normality
Confidence limits
Low-resolution plots to picture the distribution
High-resolution histograms, quantile-quantile plots, and probability plots
Frequency tables
Output data sets

44. The UNIVARIATE Procedure
Basic form of the PROC UNIVARIATE statement:
PROC UNIVARIATE options DATA= data_set_name ;
Selected options:
FREQ produces a frequency table
NOPRINT suppresses all tables of descriptive statistics; use when producing an output data set
NORMAL computes a test statistic for the hypothesis that the input data come from a normal distribution
PLOT produces a stem and leaf plot, a box plot, and a normal probability plot (all lowresolution)
ROUND specifies units for rounding variable values before computations
CIBASIC requests confidence limits for the mean, standard deviation, and variance based on normally distributed data

45. The UNIVARIATE Procedure
Selected statements used with PROC UNIVARIATE:
BY variable list ;
VAR variable list ;
FREQ variable ; Specifies a numeric variable whose values represent the frequency of the observation.
WEIGHT variable ; Specifies weight for the analysis variables.
ID variable list ; Identifies the extreme observations in the appropriate table.
OUTPUT OUT=sas_data_set output-statistic-list
PCTLPTS=percentiles PCTLPRE=prefix-name-list
PCTLNAMES=suffix-name-list ;

46. The UNIVARIATE Procedure
Basic examples
PROC UNIVARIATE DATA=sales2;
VAR price;
TITLE1 'PROC UNIVARIATE with No Options';
RUN;
PROC UNIVARIATE DATA=sales2 FREQ PLOT NORMAL ;
VAR COST ;
ID CLERK ;
LABEL COST='Total Cost' ;
TITLE1 'PROC UNIVARIATE with Several Options and Optional Statements';
RUN;

47. The UNIVARIATE Procedure
Output data set example
PROC SORT DATA=sales2 OUT=sales;
BY sex;
RUN;
PROC UNIVARIATE DATA=sales NOPRINT;
VAR cost price;
OUTPUT OUT=stats N=ncost nprice
NMISS=nmcost nmprice
MEAN=mcost mprice
MAX=maxcost maxprice ;
PROC PRINT DATA=stats;
TITLE1 'Output Data Set from PROC UNIVARIATE';

48. The MEANS Procedure
The MEANS procedure produces simple univariate descriptive statistics for numeric variables.
Selected univariate statistics
Special BY group processing: using a BY or CLASS statement will cause MEANS to calculate
descriptive statistics separately for groups of observations
Printed output optional
Output data set of summary statistics optional

49. The MEANS Procedure Basic form of the PROC MEANS statement:
PROC MEANS DATA= data_set_name options statistic-keywords;
Selected options:
FW= specifies the field width to use in printing each statistic; default is 12
NOPRINT suppresses all printed output
MAXDEC= specifies the maximum number of decimal places
MISSING requests that PROC MEANS treat missing values as valid subgroup values for the CLASS variables
NWAY specifies that statistics be output for only the observations with the highest _TYPE_ value

50. The MEANS Procedure
Selected statistic-keywords (default N, MEAN, STD, MIN, and MAX):
N number of non-missing values
NMISS number of missing values
MEAN the mean
SUM the sum of all values
STD standard deviation
STDERR standard error
VAR variance
MAX maximum
MIN minimum
CLM confidence interval for the mean
MEDIAN the median
P1 1st percentile
P5 5th percentile
P10 10th percentile
P90 90th percentile
P95 95th percentile
P99 99th percentile
Q1 25th percentile
Q3 75th percentile
T t test
PROBT p-value based on t

51. The MEANS Procedure Selected statements used with PROC MEANS:
BY variable list ;
VAR variable list ;
CLASS variable list / MISSING; MISSING option requests that missing values be treated as valid class level values.
FREQ variable ;
WEIGHT variable ;
OUTPUT OUT=sas_data_set output-statistic-list / AUTONAME;
ID variable list; Can be used to add extra variables to the output data set.

52. The MEANS Procedure: examples
Basic examples
BY-group processing / the CLASS statement
PROC MEANS DATA=sales2;
TITLE1 'PROC MEANS with No Options';
RUN;
PROC MEANS DATA=sales2 MEAN MIN MAX ;
VAR cost price ;
TITLE1 'PROC MEANS: Request Specific Statistics for Selected Variables';
RUN;
PROC SORT DATA=sales2 OUT=sales ;
BY sex;
RUN;
PROC MEANS DATA=sales N MEAN;
BY sex ;
PROC MEANS DATA=sales2 N MEAN;
CLASS sex ;
RUN;

53. The MEANS Procedure: examples
Example: Creating an output SAS data set using a BY statement (also AUTONAME)
PROC SORT DATA=sales2;
BY sex;
RUN;
PROC MEANS DATA=sales2 NOPRINT;
VAR cost price;
OUTPUT OUT=summary N= MEAN= / AUTONAME;
PROC PRINT DATA=summary;
TITLE1 'Output SAS Data Set from PROC MEANS';
TITLE2 'with the BY Statement (also AUTONAME)';

54. The MEANS Procedure: examples
Example: Creating an output SAS data set using a CLASS statement with and without the NWAY option. Note how the NWAY option affects the output data set.
PROC MEANS DATA=sales2 NOPRINT ;
CLASS sex ;
VAR cost price ;
OUTPUT OUT=summary
N=NCost NPrice
MEAN=MeanCost MeanPrice ;
RUN;
PROC MEANS DATA=sales2 NOPRINT NWAY;
CLASS sex ;
VAR cost price ;
OUTPUT OUT=summary
N=NCost NPrice
MEAN=MeanCost MeanPrice ;
RUN;

55. SAS Descriptive Procedures: Summary
SORT
Used to rearrange observations by one or more sort fields.
Must be used to sort data before a BY statement is used with other procedures.
Can sort data in ascending or descending order.
Sorts data in ASCII sorting sequence.
Can be used to check for and remove duplicate observations.
CONTENTS
Displays descriptor part of a SAS data set.
Can be used to get meta-information on existing or new SAS data sets.
To see information similar to PROC CONTENTS output, view the properties of a data set in the SAS Explorer window.
PRINT
Displays data part of a SAS data set.
Can be used to check a data set or to produce simple listing reports.
Another way to visually inspect the data portion of a data set is to use the ViewTable window. E.g., double-click on the data set in the SAS Explorer window.

56. SAS Descriptive Procedures: Summary
FREQ
Displays the distribution of variable values in tabular format.
Displays the combined frequency for two or more variables.
Displays measures of association and test statistics for two-way tables.
More appropriate for discrete variables.
Should be used to print out all of the possible values a discrete variable can have and to get a frequency distribution of each discrete variable.
UNIVARIATE
Gives detailed information about the distribution of a numeric variable.
More appropriate for continuous variables.
Should be run on any variables to be used in more analytic procedures.
Can be used to output statistics of interest.
MEANS
Provides simple univariate statistics for numeric variables.
More condensed output than UNIVARIATE.