Powerful Classes for HTTP Requests and Responses
person(given = "Thomas Lin",
family = "Pedersen",
role = c("cre", "aut"),
email = "thomasp85@gmail.com")
In order to facilitate parsing of http requests and creating
appropriate responses this package provides two classes to handle a lot of
the housekeeping involved in working with http exchanges. The infrastructure
builds upon the 'rook' specification and is thus well suited to be combined
with 'httpuv' based web servers.
R6, assertthat, stringi, urltools, tools, brotli, jsonlite,
xml2, webutils, utils

High level and easy 'HTTP' client for 'R'. Provides functions for
building 'HTTP' queries, including query parameters, body requests, headers,
authentication, and more.

Helper Package to Install Packages for R
c(person(given = "Jonathan M.",
family = "Mang",
role = c("aut", "cre"),
email = "jonathan.mang@uk-erlangen.de",
comment = c(ORCID = "0000-0003-0518-4710")),
person(given = "MIRACUM - Medical Informatics in Research and Care in University Medicine",
role = "fnd"),
person(given = "Universitätsklinikum Erlangen",
role = "cph"))
Helper function to install packages for R using an external
'requirements.txt' or a string containing diverse packages from
several resources like Github or CRAN.
Jonathan M. Mang [aut, cre] (<https://orcid.org/0000-0003-0518-4710>),
MIRACUM - Medical Informatics in Research and Care in University
Medicine [fnd],
Universitätsklinikum Erlangen [cph]

person("Peter", "van den Berg", email = "peter_v_d_berg@hotmail.com", role = c("aut", "cre"))
Modularizes source code. Keeps the global environment clean,
explicifies interdependencies. Inspired by 'RequireJS'<http://requirejs.org/>.
Peter van den Berg <peter_v_d_berg@hotmail.com>

Power and Sample Size Calculations for Completely Randomized and
Rerandomized Experiments
c(person(given = "Zach",
family = "Branson",
role = c("aut", "cre"),
email = "zach@stat.cmu.edu"),
person(given = "Xinran",
family = "Li",
role = c("aut"),
email = "xinranli@illinois.edu"))
Computes the power resulting from completely randomized and rerandomized experiments with two groups. Furthermore, computes the sample size necessary to obtain a desired level of power for completely randomized and rerandomized experiments.
Zach Branson [aut, cre],
Xinran Li [aut]