Some SAS procedures (like PROC REG, GLM, ANOVA, SQL, and IML) end with “QUIT;”, not “RUN;”

Most SAS procedures require the

RUN;

statement to signal their termination.  However, there are some notable exceptions to this.

I have written about PROC SQL many times on my blog, and this procedure requires the

QUIT;

statement instead.

It turns out that there is another set of statistical procedures that require the QUIT statement, and some of them are very common.  They are called interactive procedures, and they include PROC REG, PROC GLM, and PROC ANOVAIf you end them with RUN rather than QUIT, then you will run into problems with displaying further output.  For example, if you try to output a data set from one such PROC and end it with the RUN statement, then you will get this error message:

ERROR: You cannot open WORK.MYDATA.DATA for input access with record-level 
control because WORK.MYDATA.DATA is in use by you in resource environment 
REG.

WORK.MYDATA cannot be opened.

You will also notice that the Program Editor says “PROC … running” in its banner when you end such a PROC with RUN rather than QUIT.

I don’t like this exception, but, alas, it does exist.  You can find out more about these interactive procedures in SAS Usage Note #37105.  As this note says, the ANOVA, ARIMA, CATMOD, FACTEX, GLM, MODEL, OPTEX, PLAN, and REG procedures are interactive procedures, and they all require the QUIT statement for termination.

PROC IML is not mentioned in that usage note, but this procedure also requires the QUIT statement.  Rick Wicklin has written an article about this on his blog, The DO Loop.

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Sort a data set by ascending or descending variables using PROC SORT in SAS

Consider the built-in data set SASHELP.CLASS in SAS.  Here are the first 5 observations from PROC PRINT.

Obs Name Sex Age Height Weight
1 Joyce F 11 51.3 50.5
2 Thomas M 11 57.5 85.0
3 James M 12 57.3 83.0
4 Jane F 12 59.8 84.5
5 John M 12 59.0 99.5

As you can clearly see, they are NOT sorted by weight.  Here is how you can sort the data set by weight using PROC SORT.

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Remove leading blanks when creating macro variables using PROC SQL in SAS

I regularly use PROC SQL to create macro variables in SAS, and I recently noticed a strange phenomenon when resolving a macro variable within double quotation marks in the title of a plot.  Thankfully, I was able to replicate this problem using the SASHELP.BASEBALL data set, which is publicly available.  I was then able to send the code and the strange result to SAS Technical Support for their examination.

proc sql;
     select count(name)
     into   :hitters_100plusHR
     from   sashelp.baseball
     where  CrHome > 100;
quit;


proc sgplot
     data = sashelp.baseball;
     histogram Salary;
     title1 'Distribution of salaries';
     title2 "Restricted to the &hitters_100plusHR hitters with more than 100 career home runs";
run;

 

Here is the resulting plot.  Notice the extra spaces before “72” in the title of the plot.

SAS Technical Support informed me that

  • this problem is commonly known.
  • there is no way of predicting when it will occur
  • for now, the best way to deal with it is to remove the leading blanks using one of several ways.

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Store multiple strings of text as a macro variable in SAS with PROC SQL and the INTO statement

I often need to work with many variables at a time in SAS, but I don’t like to type all of their names manually – not only is it messy to read, it also induces errors in transcription, even when copying and pasting.  I recently learned of an elegant and efficient way to store multiple variable names into a macro variable that overcomes those problems.  This technique uses the INTO statement in PROC SQL.

To illustrate how this storage method can be applied in a practical context, suppose that we want to determine the factors that contribute to a baseball player’s salary in the built-in SASHELP.BASEBALL data setI will consider all continuous variables other than “Salary” and “logSalary”, but I don’t want to write them explicitly in any programming statements.  To do this, I first obtain the variable names and types of a data set using PROC CONTENTS.

* create a data set of the variable names;
proc contents
     data = sashelp.baseball
          noprint
     out = bvars (keep = name type);
run;

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Using PROC SQL to Find Uncommon Observations Between 2 Data Sets in SAS

A common task in data analysis is to compare 2 data sets and determine the uncommon rows between them.  By “uncommon rows”, I mean rows whose identifier value exists in one data set but not the other. In this tutorial, I will demonstrate how to do so using PROC SQL.

Let’s create 2 data sets.

data dataset1;
      input id $ group $ gender $ age;
      cards;
      111 A Male 11
      111 B Male 11
      222 D Male 12
      333 E Female 13
      666 G Female 14
      999 A Male 15
      999 B Male 15
      999 C Male 15
      ;
run;
data dataset2;
      input id $ group $ gender $ age;
      cards;
      111 A Male 11
      999 C Male 15
      ;
run;

First, let’s identify the observations in dataset1 whose ID variable values don’t exist in dataset2.  I will export this set of observations into a data set called mismatches1, and I will print it for your viewing.  The logic of the code is simple – find the IDs in dataset1 that are not in the IDs in dataset2.  The code “select *” ensures that all columns from dataset1 are used to create the data set in mismatches1.

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Vancouver SAS User Group Meeting – Wednesday, November 26, 2014, at Holiday Inn Vancouver-Centre (West Broadway)

I am pleased to have recently joined the executive organizing team of the Vancouver SAS User Group.  We hold meetings twice per year to allow Metro Vancouver users of all kinds of SAS products to share their knowledge, tips and advice with others.  These events are free to attend, but registration is required.

SAS Logo - The Power to Know

Our next meeting will be held on Wednesday, November 26, 2014.  Starting from 8:30 am, a free breakfast will be served while registration takes place.  The session will begin at 9:00 am and end at 12:30 pm with a prize draw.

Please note that there is a new location for this meeting: the East and Centre Ballrooms at Holiday Inn Vancouver-Centre at 711 West Broadway in Vancouver.  We will also experiment with holding a half-day session by ending at 12:30 pm at this meeting.  Visit our web site for more information and to register for this free event!

If you will attend this event, please feel free to come and say “Hello”!

Read the rest of this post for the full agenda!

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