metagear (version 0.1)

abstract_screener: A GUI screener to quickly code candidate studies for inclusion/exclusion into a systematic review or meta-analysis.

Description

A GUI screener to help scan and evaluate the title and abstract of studies to be included in a systematic review or meta-analysis.

Usage

abstract_screener(file = file.choose(), aReviewer = NULL,
  reviewerColumnName = "REVIEWERS", unscreenedColumnName = "INCLUDE",
  unscreenedValue = "not vetted", abstractColumnName = "ABSTRACT",
  titleColumnName = "TITLE")

Arguments

file

The file name and location of a .csv file containing the abstracts and titles. The .csv file should have been initialized with /code{effort_initialize} and populated with screeners (reviewers) using /code{effort_distribute}.

aReviewer

The name (a string) of the reviewer to screen abstracts. It is used when there are multiple reviewers assigned to screen abstracts. The default column label is "REVIEWERS" as initialized with /code{effort_distribute}.

reviewerColumnName

The name of the column heading in the .csv file that contains the reviewer names that will screen abstracts. The default column label is "REVIEWERS".

unscreenedColumnName

The name of the column heading in the .csv file that contains the screening outcomes (i.e. vetting outcomes by a reviewer). Unscreened references are by default labeled as "not vetted". The reviewer then can code to "YES" (is a relevant study), "NO" i

unscreenedValue

Changes the default coding (a string) of "not vetted" that designates whether an abstract remains to be screened or vetted.

abstractColumnName

The name of the column heading in the .csv file that contains the abstracts. The default label of this column is "ABSTRACT".

titleColumnName

The name of the column heading in the .csv file that contains the titles. The default label of this column is "TITLE".

Examples

data(example_references_metagear)
effort_distribute(example_references_metagear,
                  initialize = TRUE, reviewers = "marc", save_split = TRUE)
abstract_screener("effort_marc.csv", aReviewer = "marc")