effort_initialize: Formats a reference dataset for title/abstract screening...

In metagear: Comprehensive Research Synthesis Tools for Systematic Reviews and Meta-Analysis

Description

Adds columns with standardized labels to a data framw with bibliographic data on journal articles. These columns will be used to assign reviewers, implementation of dual screening design, and the coding of inclusion/exclusions screening decisions.

Usage

effort_initialize(
  aDataFrame,
  study_ID = TRUE,
  unscreenedValue = "not vetted",
  dual = FALSE,
  front = TRUE
)

Arguments

aDataFrame	A data.frame object that includes the titles and abstracts to be screened. It will be formatted for screening efforts. See example: example_references_metagear
study_ID	When FALSE, does not add a column "STUDY_ID" that includes a unique identification number for each reference (row) in the dataFrame.
unscreenedValue	Changes the default coding (a string) of "not vetted" that designates whether an abstract remains to be screened or vetted as part of the "INCLUDE" column.
dual	When TRUE, formats dataFrame for a dual screening (paired) design. Creates two reviewer teams: REVIEWERS_A and REVIEWERS_B.
front	When FALSE, adds new columns to the back end of the dataframe. When TRUE, adds columns to the front.

Value

A data.frame formatted for title/abstract screening efforts.

See Also

effort_distribute, effort_merge, effort_summary

Examples

data(example_references_metagear)
effort_initialize(example_references_metagear)        

metagear documentation built on Feb. 15, 2021, 5:09 p.m.