[R] R validation. If you know what you want, it's simple. If you don't know what you need to do, there are problems...(with any validation)

[A.J. Rossini]

> From: delphine.fontaine at genexion.com
> To: r-help at stat.math.ethz.ch
> Date: Sat, 3 Nov 2007 09:03:39 +0100 (CET)
> Subject: [R] R validation
> Dear R-Users,
>
> A message to continue the discussions we had in March and June. I have
> read the documents written since then
> (http://www.r-project.org/doc/R-FDA.pdf ;
> http://user2007.org/program/presentations/harrell.pdf ;
> http://user2007.org/program/presentations/rossini.pdf ;
> http://user2007.org/program/presentations/soukup.pdf) which are very
> interesting and useful.
>
> I work in a CRO and we strongly believe that R could be our standard
> statistical tool for all our analyses. I agree that it is more relevant
> (and easier) to validate an analysis than the whole software but anyway,
> if we want to systematically use R, we must convince our top management
> first and then our clients that R is reliable. Most of them do not know
> the R environment and it is more that likely that we will be asked for any
> validation documentation.
>
> I am sure that the Core team has thoroughly tested "Base R" functions and
> the recommended packages. Is it possible to have access to the scripts or
> any documents that would attest that R gives reliable/validated results ?
> All the discussions, documents mentioned above are a big step for the use
> of R in the pharma/biotech environment but I also think that validation
> documents or scripts are indispensable to convince our top management, our
> clients and regulatory bodies.
>
> If validation documentation or scripts do not exist or are not available,
> could anyone tell me in concrete terms which are the minimum requirements
> to validate R functions or packages ?

Please read again, you are missing something.

R comes with IQ if you build your own.

All other validation and qualification scripts will need to be
specified by the relevant concerned parties in your company.

i.e. to answer the questions, "what do we require", "what
specifications must be met", etc, for a relevant subset of things that
must be required and specs that must be met for this to meet your
needs.

Good practice is to establish your needs, and then verify that you've
met them.

Of course, you can outsource the whole thing, there are some very good
companies that can help with this, who can tell you what
specifications you want to meet, and what you will require.  In my
opinion, they might even be able to do it without going too wrong.

(disclaimer: I work for one of the largest pharmas as a pointy-headed
boss, and my group (not clin statistics, but in clinical development
and on the regulated side) will be using R and Linux for clinical work
as soon as we (well, I) finish some paperwork.   Of course, read
Dilbert if you think I'm making any sense...).

best,
-tony

blindglobe at gmail.com
Muttenz, Switzerland.
"Commit early,commit often, and commit in a repository from which we
can easily roll-back your mistakes" (AJR, 4Jan05).