Question: As science must be reproducible, by definition, there is increasing recognition that data and code are an essential component of the reproduciblity, as discussed by the [Yale Roundtable for data and code sharing](http://reproducible-research.googlegroups.com/web/CISE-12-5-News.pdf).

In reviewing a manuscript for a journal that does not require data and code sharing, can I request that the data and code be made available 

1. to me at the time of review
2. publicly at time of publication (the journal supports supplements)

also, how might I phrase such a request?

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*update*: although I am interested in the general case, this particular case consists of a meta-analysis with all previously published data, and the code is simple linear models in SAS

*side note* the ability to make cross-study inference (as is the goal of meta-analysis) would be greatly enhanced if more studies provided raw data 

*update 2*: 

I requested the data and code from the editor for purposes of review, the editor considered the request reasonable, and I have received the requested material (sufficient but with cryptic variable names, no metadata, and few inline comments) within a day.

Answer: 
Addressing the two situations seperately:

As a reviewer: Yes, I think you'd have grounds to ask to see the data or the code. But if I were you, I'd prepare to see things like pared down code, or a subsample of the data. People implement future research not being reported in this paper in their code all the time, and you've no entitlement to said code. Since I do mostly biomedical research, I'd also be prepared to have to deal with some fairly restrictive data use agreements.

In the journal itself: No. If a researcher wants to reproduce my results, they can approach me themselves to ask for code - that's why we have corresponding authors. For data, absolutely not, under no circumstances. My data is governed by IRB and confidentiality agreements - it's not just going to be made public. If I *want* a public-ish data set, I might simulate a dataset with similar properties (i.e. the "Faux-Mesa" network data available in one of the network packages for R), but as a reviewer, you've got no call to force that. If its a journal-wide requirement, then the authors knew their data/code would be public when submitting it, but if its not then no. Your role is to evaluate the quality of the paper itself (hence my being alright with it for the purposes of the review), not use your ability to contribute to the acceptance/rejection of the paper to push what is essentially a philosophical/political point outside the scope of the journal.

At best, I'd put a "I would strongly urge the authors to make their code and data available, where possible" in your comments, but I wouldn't phrase it any stronger than that, and I wouldn't put it in the formal list of "Things I think need fixing before this sees the light of day".
I don't have any experience with this, but it seems to me that you might be able to insist on #1 as a part of your own due diligence in reviewing their results. I don't see how you can insist on #2, though.