sample_references: Random sample references

In AIscreenR: AI Screening Tools in R for Systematic Reviewing

Random sample references

Description

sample_referencessamples n rows from the dataset with titles and abstracts either with or without replacement. This function is supposed to support the construct of a test dataset, as suggested by Vembye et al. (2025).

Usage

sample_references(
  data,
  n,
  with_replacement = FALSE,
  prob_vec = rep(1/n, nrow(data))
)

Arguments

data	Dataset containing the titles and abstracts wanted to be screened.
n	A non-negative integer giving the number of rows to choose.
with_replacement	Logical indicating if sampling should be done with of without replacement. Default is FALSE.
prob_vec	'A vector of probability weights for obtaining the elements of the vector being sampled.' Default is a vector of 1/n.

Value

A dataset with n rows.

References

Vembye, M. H., Christensen, J., Mølgaard, A. B., & Schytt, F. L. W. (2025). Generative Pretrained Transformer Models Can Function as Highly Reliable Second Screeners of Titles and Abstracts in Systematic Reviews: A Proof of Concept and Common Guidelines. Psychological Methods. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1037/met0000769")}

Examples

excl_test_dat <- filges2015_dat[1:200,] |> sample_references(100)

AIscreenR documentation built on April 13, 2026, 5:08 p.m.