hi,
first up let me apologise for breaking the thread. i subscribed to this
list after the initial email went out.
i'm not completely sure if the original post was to prompt a discussion
here, but now there's a discussion, i'm jumping in!
i'm a psychologist, and one of the challenges is the number of packages
required to do what is "standard practice", and getting them all to work
together.
to do an ANOVA (the bread and butter of psych research) with all it's
assumption checks, contrasts, corrections, etc. requires in the order of
seven packages.
our solution to this is to create an "uber" package, which makes use of
all these things behind a single function call (with many arguments),
which is what our jmv package is:
https://www.jamovi.org/jmv/
we represent an extreme, we even handle plots, but there are other
examples of more intermediate solutions: afex, psych, etc.
i appreciate this is somewhat at odds with (what i perceive to be) the R
ethos, which is giving people very fine control over the intermediate
parts of one's analysis, but it is another approach to making it easier
for people to find appropriate tools for their field.
for me, the key is being "goal-centred", "what is a person in my field
trying to achieve?" rather than "analysis-centred"; "this package
provides analysis X" ... but i appreciate this is likely an unpopular
position.
i'll definitely be attending this session at use!R, and happy to espouse
more unpopular views
cheers
jonathon
Navigating the Jungle of R Packages
The R ecosystem has many packages in various collections,
especially CRAN, Bioconductor, and GitHub. While this
richness of choice speaks to the popularity and
importance of R, the large number of contributed packages
makes it difficult for users to find appropriate tools for
their work.
A session on this subject has been approved for UseR! in
Brussels. The tentative structure is three short
introductory presentations, followed by discussion or
planning work to improve the tools available to help
users find the best R package and function for their needs.
The currently proposed topics are
- wrapper packages that allow diverse tools that perform
similar functions to be accessed by unified calls
- collaborative mechanisms to create and update Task Views
- search and sort tools to find packages.
At the time of writing we have tentative presenters for
the topics, but welcome others. We hope these presentations
at useR! 2017 will be part of a larger discussion that will
contribute to an increased team effort after the conference
to improve the the support for R users in these areas.
John Nash, Julia Silge, Spencer Graves
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