Delphine Fontaine wrote:
> Thanks for your answer which was very helpfull. I have another question:
>
> I have read in this document
> (http://cran.r-project.org/doc/manuals/R-intro.pdf) that most of the
> programs written in R are ephemeral and that new releases are not
> always compatible with previous releases. What I would like to know is
> if R functions are already validated and if not, what should we do to
> validate a R function ?
>
In the sense in which most persons use the term 'validate', it means to
show with one or more datasets that the function is capable of producing
the right answer. It doesn't mean that it produces the right answer for
every dataset although we hope it does. [As an aside, most errors are
in the data manipulation phase, not in the analysis phase.] So I think
that instead of validating functions we should spend more effort on
validating analyses [and validating analysis file derivation]. Pivotal
analyses can be re-done a variety of ways, in R or in separate
programmable packages such as Stata.
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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