bate_2019_srq

8,300 responses from 415 respondents to 20 items.

About this table

DescriptionSuper-Recognizer Questionnaire (SRQ), 20 self-report items on a 1-5 scale; 415 adults pooled from a top-end civilian sample (n=264) and a police sample (n=151).
ReferenceBate S, Dudfield G. 2019. Subjective assessment for super recognition: an evaluation of self-report methods in civilian and police participants. PeerJ 7:e6330.
DOI10.7717/peerj.6330
LicenceCC BY 4.0
Source datahttps://peerj.com/articles/6330/#supplementary-material

Size and shape

Responses8,300
Respondents415
Items20
Response categories5
Responses per respondent20
Responses per item415
Density1
LongitudinalFALSE

Columns

cov_agecov_gendercov_groupcov_studyiditemresp

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("bate_2019_srq")
# Python
pip install irw

import irw
df = irw.fetch("bate_2019_srq")

How to cite

@article{Bate_2019, title={Subjective assessment for super recognition: an evaluation of self-report methods in civilian and police participants}, volume={7}, ISSN={2167-8359}, url={http://dx.doi.org/10.7717/peerj.6330}, DOI={10.7717/peerj.6330}, journal={PeerJ}, publisher={PeerJ}, author={Bate, Sarah and Dudfield, Gavin}, year={2019}, month=Jan, pages={e6330} }

Version and provenance

IRW versionv439
Redivis datasetitem_response_warehouse_6 v3.7
Redivis dataset DOI10.57761/k0pn-7r67
Manifest pin for this IRW versionv3.6
Metadata sourceirw_meta v27.0