The R tag covers an enormous number of questions, many of which aren't really about R in general, but how to use a specific package. There appear to have already been some grumblings about this in meta already:

Syntax highlighting with r tag

Should tags refer to the answer as well as the question?(see comment)

As I see it there are broadly three types of R question

Type A

Some questions that validly fit into a general R tag:

Difference between logit and probit models (questioner request an R answer)

Free resources for learning R

Type B

But other questions could be cut down to a more specific tag (as has been suggested at times, see meta examples above), for example:

Interpretation of R's lm() output (could be tagged lm)

Cost function for validating Poisson regression models(Is also tagged cv.glm)

Type C

While others use R heavily in the question example, but don't actually need R

Removal of statistically significant intercept term increases $R^2$ in linear model

How to interpret type I, type II, and type III ANOVA and MANOVA?

Which questions should be tagged as R?

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    $\begingroup$ I answered my own question simply to separate my opinion from the issue itself, hope that's ok. I'd be really interested to see if people think differently (clearly some people MUST think type C questions should be tagged R - the people that asked them!) $\endgroup$ – Korone Feb 2 '13 at 12:12

A risk of adding package tags would be 1) overlapping nomenclature 2) frequent disagreement on tags and 3) difficulty consulting relevant questions from other tagged questions with answers. For instance, a user working with the survey package would probably often mistakenly use the survey tag instead of the survey-package tag. If a user tags their question with ggplot2 but the source of their problem was a data formatting issue, then should the ggplot2 tag be removed, even if the subtlety in data formatting was unique to that package? It could also greatly inflate the number of tags, leading to an overly granular approach to browsing questions (such as packages with overlapping functionality like lme4 and nlme or gee, geese, and sandwich for computing robust standard errors).

I think R packages come and go and there are way too many of them. I also think many expert statisticians can quickly look up documentation on a few package specific questions and quickly address the users questions without even downloading that package.

I think questions of type C which are methodological in nature but rely upon R to convey the idea and are tagged as such are in serious need of quality improvement. It seems that currently, expert users migrate these posts to stackoverflow where they often languish and die. I think experts should be more assertive in editing such posts to remove code/unformatted output that can be explained in concepts or algebra.

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  • $\begingroup$ Totally agree with your point about packages. $\endgroup$ – Korone Feb 11 '13 at 23:23
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    $\begingroup$ Given the current 'anti-R' sentiment associated with rampant migration of (what I consider to be) on-topic questions, it doesn't make sense to have package specific tags. If sentiment changes as the number of 4k+ karma users increases, then it might be worth re-opening the discussion. $\endgroup$ – russellpierce Feb 12 '13 at 15:45
  • $\begingroup$ As a precursor to that (hopefully) future discussion, I'll say that if a package is required in the example, it makes sense to tag it even if the solution turns out to not be a problem with the package itself. In short, tags should reflect the question, not the answer. $\endgroup$ – russellpierce Feb 12 '13 at 15:51
  • $\begingroup$ The misuse of "survey" versus "survey-package" can be sorted out by admins and experience. Questions should be tagged with both R-relevant and statistical-technique relevant tags. So I'm not worried about overly granular approaches. I agree there are a lot of R packages, but quite a few are large enough to warrant their own tag. $\endgroup$ – russellpierce Feb 12 '13 at 15:51

I don't think type C questions should be tagged R. Surely R tags should be for questions that require knowledge of R to answer - R is not a hard syntax, so for the examples above many non R users would understand and be able to answer the question. I don't think syntax highlighting is important enough, and anyway most people put the output in as well, which always highlights wrong (e.g. the "Interpretation of R's lm() output" link above).

Type B questions I'm more unsure of. On the one hand, they create an enormous number of R tags, but on the other hand they do need some R expertise. If there are any answerers who follow the R feed because they have lots of R experience, then it is important these are tagged as R. On balance I would say they should be tagged R.

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If this is a strictly R programming/implementation question, it should go to SO. If this is a true statistics question, then an R package is just an implementation of the method, and one can often find alternative implementations in Stata, SAS, Matlab, or even (God forbid) Excel. So instead of cv.glm tag in the second type B question, it should have been the methods cross-validation tag. Any of the *lme* questions are actually mixed-model questions, etc.

On a number of occasions, I wrote in the tag excerpt something like "this tag is too generic, please use this for this, and that for that" (see, e.g., multilevel and gmm tags... I think the latter was actually killed, which isn't right, and should still be sitting around as a redirect). May be it is time to do something like this with r: officially declare R to be the default statistical package to ask questions about and give examples in, discourage the use of the r tag, and tell the users to use a tag like learning-r for the second question in A and the first question in B. Some other tags may need to be devised for "valid" R questions that CV rather than SO should handle, e.g., compare-stat-packages for tag combos like https://stats.stackexchange.com/questions/tagged/r+sas or https://stats.stackexchange.com/questions/tagged/r+stata.

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    $\begingroup$ What about the syntax highlighting that comes along with the R tag though? $\endgroup$ – Korone Feb 12 '13 at 23:22
  • $\begingroup$ Hm. I was not aware of syntax highlighting. Can you point to an example? $\endgroup$ – StasK Feb 13 '13 at 0:01
  • $\begingroup$ See: stats.stackexchange.com/q/33917/19879 compared to stats.stackexchange.com/q/10943/19879 $\endgroup$ – Korone Feb 13 '13 at 0:06
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    $\begingroup$ Hm. Once again, was not aware. However, using a tag to achieve syntax highlighting is a bad smell, speaking in computer science terms: it uses a (poorly documented) backdoor functionality that a function produces for some other reason. Syntax highlighting should be a checkbox that the user could check when posting the question. Or define r-syntax-highlight tag for this purpose specifically if needed; r is too general. I imagine nobody bothered defining syntax highlighting for Stata or SAS. $\endgroup$ – StasK Feb 13 '13 at 0:10
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    $\begingroup$ I guess this is carried over from SO where most languages have their own highlighting schemes linked to tags. Probably makes a lot more sense on SO $\endgroup$ – Korone Feb 13 '13 at 7:35
  • $\begingroup$ +1 I agree (and to be frank who gives a crap about syntax highlighting here). The current r tag is used so indiscriminately it is near worthless. I think at this point I would personally prefer to ban all of the stat software tags here. You can just use the generic search to replace them if needed. $\endgroup$ – Andy W Feb 13 '13 at 13:56

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