distribute_tasks.Rd
A common task in systematic review is to divide a dataset of articles located by a search (typically involving >1 databases) and distributing them amongst a team of reviewers for screening. This function takes a dataset divides it among the specified number of reviewers, returning the resulting data.frames either in a list to the workspace, or (by default) as a set of .csv files in the specified directory. The resulting files can be passed to any of the screening functions provided by revtools, i.e. screen_titles
, screen_abstracts
, or screen_topics
.
distribute_tasks(data, reviewers, write_csv = TRUE,
file_name = "reviewer.csv", return_data = FALSE, ...)
a vector of strings
Either a data.frame
as returned by allocate_effort
, an integer giving the number of reviewers, or a vector of strings giving reviewer names.
Logical - should the function write a set of csv files (1 per reviewer)? Defaults to TRUE
a file path & name showing where .csv files should be saved. Ignored if write_csv
is FALSE. Defaults to 'reviewer_[name].csv'.
Logical - should a list be (invisibly) returned, in which each entry is the data sent to a single reviewer? Defaults to FALSE.
Further arguments passed to allocate_effort
Invisibly returns a list of data.frames, each with same columns as data
but containing only a subset of rows.
The dataset is allocated each author in the proportion of articles specified by allocate_effort
, with the identity of articles passed to reviewer being chosen by rnorm
. As a result, this function is very sensitive to the inputs provided to allocate_effort
, so it is often worth running that function first and checking the results to be certain that effort is being distributed in a way that you are happy with.
allocate_effort
for a detailed description of how the division among reviewers is accomplished.
# import some data
file_location <- system.file(
"extdata",
"avian_ecology_bibliography.ris",
package = "revtools")
x <- read_bibliography(file_location)
result <- distribute_tasks(x, 4, write_csv = FALSE) # split evenly among 4 reviewers