# Citing R or SAS

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One of us recently read a colleague’s first draft of a paper, in which she had written: “All analyses were done in R 2.14.0.” We assume we’re preaching to the converted here, when we say that the enormous amount of work that goes into R needs to be recognized as often as possible, and that R’s creators deserve to reap some credit for their labors. In contrast to SAS, after all, most work on R is not compensated with a paycheck. As a reminder, the **SAS and R**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

`citation()`function produces the correct citation for R in general and is good to use when citing R.

The project in question had used a negative binomial regression function from the MASS package, but colleague had omitted any reference to it. In this case, a citation would provide both credit to the authors and a useful guide to anyone wanting to replicate our approach. It would also allow readers to consider whether changes in the package might affect the results observed. A call to

`citation(package="MASS")`will provide the preferred citation here. (Any package name can be inserted, or course, though some authors may not have provided a full citation.)

Similarly, while SAS authors are rarely identified by name and presumably get a salary from SAS, it’s preferable to identify the version of the software and where it can be obtained. In medical research this is usually done by an in-text reference. For example: “Analyses were performed in SAS 9.3 (SAS Institute, Cary NC).”

For complex analyses, it is also best to mention the SAS procedure used. As with the R package, this can help readers plan similar analyses, and may inform interpretation.

So a multi-software analysis section might end with the following statement: Analyses were performed in R 2.14.2 [1] using the MASS package [2]

`glm.nb()`function for negative binomial regression and in SAS 9.3 (SAS Institute, Cary NC) using the MCMC procedure for negative binomial mixture models.” The references to [1] and [2] would be found using the

`citation()`function.

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