The paper looks at the problems which can be caused when non-printable and special characters such as line feeds and carriage returns are present in SAS datasets, how to detect them and how to replace the.

Non printable and special characters can be a source of confusion when they are encountered in SAS, the programmer often only detects them by chance when they notice that the alignment in an output report seems to be disrupted for no apparent reason. A systematic approach to detecting and handling special characters is clearly required in situations when special characters can be reasonably expected and this is just what is set out in this paper.

The paper describes a clear approach for detecting special characters and explains three keyapproaches for dealing with them:

1. Report them to data management and get clean data in the next transfer.
2. Replace NPSC with other characters.
3. Delete NPSC.

Particularly useful is the recommendation to use the compress option with the ‘KW’ modifier (new to SAS version 9) to only keep writable characters.

The paper includes several worked examples as well as useful code fragments.

The paper was presented at the PharmaSUG conference in Orlando 2010. Download the paper here.

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The paper explores how the FEEDBACK option can be used in the SQL statement  to cause SAS to create additionally detailed log entries which can be useful for debugging. It explains  how use of the FEEDBACK option will cause SAS to write expanded, more explicit messages in the log, which for example explicitly list any variables that were implicitly selected with a SELECT * construction.

We particularly liked the Code Generation section in which Borowiak’s suggests using the FEEDBACK option in combination with the VALIDATE statement to write an expanded version of the SELECT * statement into the log, which can then be copied back into the program and executed.

We feel the paper is suitable for all SAS users who utilise, or are learning SQL.

The paper was presented at the SouthEast SAS® Users Group, 2012 Conference in Raleigh-Durham, North Carolina. Download the paper from the SESUG website.

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The paper explains how Proc Format can be used to combine information from multiple datasets in place  of the traditional “sort/sort/merge” approach and shows how this approach can offer reductions in CPU time of >70% when dealing with large files. In the pharma world this approach has many possible usages. Consider for example the need to look up the RFSTDTC variable in SDTM.DM and merge it onto each of your SDTM datasets in ordering to derive study day variables. Using the author’s approach would instead involve building a format from SDTM.DM which maps USUBJID to RFSTDTC. RFSTDTC can then be attached within the DATAstep using a PUT statement.  

We feel that this approach is particularly relevant now that the widespread adoption of the ADaM model means that companies are having to deal with ever larger analysis datasets. A nice feature of the paper is its proposal for merging with more than one variable.

The paper was presented in the Coder’s Corner section of the SAS Global Forum  2012 Conference in Orlando. Download the paper from Lex Jansen.

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