Hi all,
One relatively easy solution is to include R and all relevant versions
of packages used in (a) a reproduction archive and/or (b) packaged
inside a virtual machine. With storage space cheap and sources of both
R and packages available (and easy free crossplatform virtual machine
solutions and Linux) one can distribute not only ones own code and
data but also all that was required to do the analyses down to the OS.
So far in our own work we've just included relevant package versions
but we will probably start include R as well for next projects.
Hope this brainstorm helps (and credit to Ben Hansen and Mark
Fredrickson for these ideas).
Jake
Jake Bowers
http://jakebowers.org
On Jan 10, 2009, at 1:19 PM, "Nicholas Lewin-Koh"
wrote:
Hi,
Unfortunately one of the the cornerstones of the validation paradigm
in the clinical world (as I understand it) is that
consistency/repeatability,
documentation (of the programs consistency and maintenance) and
adherence to regulatory
requirements take supremacy even ironically over correctness. So you
still
get ridiculous requirements from regulatory bodies like type III
sums of
squares, Last observation carried forward, etc. These edifices are
very hard to change, I know of people who have worked their whole
careers just to get the FDA to allow other treatment of missing data.
So what does this have to do with R? This comes down to the point
you made below about the R development cycle incorporating bug fixes
into new releases, and not supporting old versions. I think this has
been rehashed many times, and is not likely to change. So how to
move R into the clinic? From a practical perspective all the
development and interoperability features of R are very nice,
but how to maintain things in a way that if the underlying
R platform changes the tool or method does not, and furthermore
how to manage this in a cost effective way so that it can't
be argued that it is cheaper to pay for SAS???
These are not necessarily questions that R core has to answer,
as the burden of proof of validation is really in the hands of the
company/organization doing the submission. We just like to pretend
that
the large price we pay for our SAS support means we can shift
liability
:)
Rambling again,
Nicholas
On Fri, 09 Jan 2009 17:07:31 -0600, "Kevin R. Coombes"
said:
Hi Nicholas,
You raise a very good point. As an R user (who develops a couple of
packages for our own local use), I sometimes find myself cringing in
anticipation of a new R (or BioConductor) release. In my perception
(which is almost certainly exaggerated, but that's why I emphasize
that
it is only an opinion), clever theoretical arguments in favor of
structural changes have a tendency to outweigh practical
considerations
of backwards compatibility.
One of my own interests is in "reproducible research", and I've been
pushing hard here at M.D. Anderson to get people to use Sweave to
enhance the reproducibility of their own analyses. But, more often
than
I would like, I find that reports written in Sweave do not survive
the
transition from one version of R to the next, because either the core
implementation or one of the packages they depend on has changed in
some
small but meaningful way.
For our own packages, we have been adding extensive regression
testing
to ensure that the same numbers come out of various computations, in
order to see the effects of either the changes that we make or the
changes in the packages we depend on. But doing this in a nontrivial
way with real data leads to test suites that take a long time to run,
and so cannot be incorporated in the nightly builds used by CRAN.
We also encourage our analysts to include a "sessionInfo()" command
in
an appendix to each report so we are certain to document what
versions
of packages were used.
I suspect that the sort of validation you want will have to rely on
an
extensive regression suite test to make certain that the things you
need
remain stable from one release to another. That, and you'll have to
be
slow about upgrading (which may mean foregoing support from the
mailing
lists, where a common refrain in response to bug reports is that "you
aren't using the latest and greatest version", without an
appreciation
of the fact that there can be good reasons for not changing something
that you know works).
Best,
Kevin
Nicholas Lewin-Koh wrote:
Hi,
Kudos, nice exposure, but to make this more appropriate to R-devel I
would just
like to make a small comment about the point made by the SAS
executive
about getting
on an airplane yada yada ...
1) It would seem to me that R has certification documents
2) anyone designing airplanes, analyzing clinical trials, etc. had
better be worried about a lot more than whether their software is
proprietary.
So from that point of view it would seem that R has made great
strides
over
the last 5 years especially in establishing a role for op
