[R] R in the NY Times
marc_schwartz at comcast.net
Sun Jan 11 18:08:48 CET 2009
on 01/10/2009 01:50 PM Kingsford Jones wrote:
> The reactions to the NYT article have certainly made for some
> interesting reading.
> Here are some of the links:
> several posts on Andrew Gelman's blog:
> comments here: http://bits.blogs.nytimes.com/2009/01/08/r-you-ready-for-r/
> It's too bad that SAS has reacted to the negative reactions to their
> NYT quote with more FUD. The quote that Tony posted is just a
> thinly-veiled jab at R (veiled by a disingenuous "we value open
> source" veneer). Perhaps SAS is shooting themselves in the foot with
> their reactions; aren't they making it harder if they should ever
> decide the best thing to do is to embrace R and the philosophies
> behind it? Four years ago, Marc Schwartz posted interesting comments
> realted to this:
Thanks for pointing this out Kingsford. The books referenced there are
excellent for providing an understanding of the dynamics that have been
the subject of many of these threads here since the NYT article was
There is a natural tension between leading edge adopters, the "main
stream" and the laggards. Moore's "Crossing the Chasm" provides good
insights into this tension and the acceptance of new products and
Grove's "Only the Paranoid Survive" shows how individual companies and
even entire industries (think banking and autos today) can suddenly face
an unexpected risk to their survival when they fail to comprehend
marketplace dynamics and take appropriate action.
Microsoft's mis-steps vis-a-vis Vista opened the door for Apple and
Linux to increase their respective marketshare and for open source more
generally (eg. Firefox).
BTW, readers might find this commentary of interest:
Commentary: Create a tech-friendly U.S. government
By Jimmy Wales and Andrea Weckerle
> On another note, I wonder why in the various conversations there seems
> to be pervasive views that a) the FDA won't accept work done in R, and
> b) SAS is the only way to effectively handle data?
I strongly believe that the comments regarding R and the FDA are overly
negative and pessimistic.
The hurdles to the use of R for clinical trials are shrinking. There has
been substantive activity over the past several years, both internally
at the FDA and within the R community to increase R's acceptance in this
At the Joint Statistical Meetings in 2006, Sue Bell from the FDA spoke
during a session with a presentation entitled Times 'R' A Changing: FDA
Perspectives on Use of "Open Source". A copy of this presentation is
In 2007, during an FDA committee meeting reviewing the safety profile of
Avandia (Rosiglitazone), the internal FDA meta-analysis performed by Joy
Mele, the FDA statistician, was done using R. A copy of this
presentation is available here:
Given the high profile nature of drug safety issues today, that R was
used for this analysis by the FDA itself speaks volumes.
Also in 2007, at the annual R user meeting at Iowa State University, I
had the pleasure and privilege of Chairing a session on the use of R for
clinical trials. The speakers included Frank Harrell (well known to R
users here), Tony Rossini and David James (Novartis Pharmaceuticals) and
Mat Soukup (FDA statistician). Copies of our presentations are available
here, a little more than half way down the page:
At that meeting, we also introduced a document that has been updated
since then and approved formally by the R Foundation for Statistical
Computing. The document provides guidance for the use of R in the
regulated clinical trials domain, addresses R's compliance with the
relevant regulations (eg. 21 CFR 11) as well as describing the
development, testing and quality processes in place for R, also known as
the Software Development Life Cycle.
That document is available here:
I have heard directly from colleagues in industry that this document has
provided significant value in their internal discussions regarding
implementing the use of R within their respective environments and
assuaging many fears regarding R's use.
Additionally, presentations regarding the use of open source software
and R specifically for clinical trials have been made at DIA and other
industry meetings. This fall, there is a session on the use of R
scheduled for the FDA's Industry Statistics Workshop in Washington, D.C.
For those unfamiliar, I would also point out the membership and
financial donors to the R Foundation for Statistical Computing and take
note of the plethora of large pharma companies and clinical research
The use of R within this domain is increasing and will only continue to
progress as R's value becomes increasingly clear to even risk averse
industry decision makers.
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