[R] Rating R Helpers

[Ben Bolker]

John Sorkin wrote:
> 
> I believe we need to know the following about packages:
> (1) Does the package do what it purports to do, i.e. are the results
> valid?
> (2) Have the results generated by the package been validate against some
> other statistical package, or hand-worked example?
> (3) Are the methods used in the soundly based?
> (4) Does the package documentation refer to referred papers or textbooks?
> (5) In addition to the principle result, does the package return ancillary
> values that allow for proper interpretation of the main result, (e.g. lm
> gives estimates of the betas and their SEs, but also generates
> residuals)?.
> (6) Is the package easy to use, i.e. do the parameters used when invoking
> the package chosen so as to allow the package to be flexible?
> (7) Are the error messages produced by the package helpful?
> (8) Does the package conform to standards of R coding and good programming
> principles in general?
> (9) Does the package interact will with the larger R environment, e.g.
> does it have a plot method etc.?
> (10) Is the package well documented internally, i.e. is the code easy to
> follow, are the comments in the code adequate?
> (11) Is the package well documented externally, i.e. through man pages and
> perhaps other documentation (e.g. MASS and its associated textbook)?
> 
> 

Numbers 1 to 3 are critical.  The rest would be very nice to know (and
should be part of a rating
system), but in the end are more likely to lead to frustration than outright
errors ... (i.e., you'll
find out soon enough if a package is poorly documented, then you just won't
use it).

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