Computations over Distributed Data without Aggregation
utils, shiny, httr, digest, jsonlite, stringr, R6 (>= 2.0)
c(person("Balasubramanian", "Narasimhan", role=c("aut", "cre"),
email = "naras@stat.Stanford.EDU"),
person("Marina", "Bendersky", role=c("aut")),
person("Sam", "Gross", role=c("aut")),
person(c("Terry", "M."), "Therneau", role=c("ctb")),
person("Thomas", "Lumley", role=c("ctb")))
Implementing algorithms and fitting models when sites (possibly remote) share
computation summaries rather than actual data over HTTP with a master R process (using
'opencpu', for example). A stratified Cox model and a singular value decomposition are
provided. The former makes direct use of code from the R 'survival' package. (That is,
the underlying Cox model code is derived from that in the R 'survival' package.)
Sites may provide data via several means: CSV files, Redcap API, etc. An extensible
design allows for new methods to be added in the future. Web applications are provided
(via 'shiny') for the implemented methods to help in designing and deploying the
computations.
Balasubramanian Narasimhan [aut, cre], Marina Bendersky [aut],
Sam Gross [aut], Terry M. Therneau [ctb], Thomas Lumley [ctb]

utils, shiny, httr (>= 1.0.0), digest, jsonlite, stringr, R6
(>= 2.0)
Balasubramanian Narasimhan [aut, cre],
Marina Bendersky [aut],
Sam Gross [aut],
Terry M. Therneau [ctb],
Thomas Lumley [ctb]

Implementing algorithms and fitting models when sites (possibly remote) share
computation summaries rather than actual data over HTTP with a master R process (using
'opencpu', for example). A stratified Cox model and a singular value decomposition are
provided. The former makes direct use of code from the R 'survival' package. (That is,
the underlying Cox model code is derived from that in the R 'survival' package.)
Sites may provide data via several means: CSV files, Redcap API, etc. An extensible
design allows for new methods to be added in the future and includes facilities
for local prototyping and testing. Web applications are provided (via 'shiny') for
the implemented methods to help in designing and deploying the computations.