enkavi_2019_stopsignal

403,800 responses from 523 respondents to 16 items.

About this table

DescriptionStop-signal task (high/low delay condition, go/stop trials), trial-level accuracy + RT, N=523, baseline + retest waves
ReferenceEnkavi, A. Z., Eisenberg, I. W., Bissett, P. G., Mazza, G. L., MacKinnon, D. P., Marsch, L. A., & Poldrack, R. A. (2019). Large-scale analysis of test-retest reliabilities of self-regulation measures. Proceedings of the National Academy of Sciences, 116(12), 5472-5477. https://doi.org/10.1073/pnas.1818430116
DOI10.1073/pnas.1818430116
LicenceCC BY 4.0
Source datahttps://github.com/IanEisenberg/Self_Regulation_Ontology/tree/master/Data

Size and shape

Responses403,800
Respondents523
Items16
Response categories2
Responses per respondent772.084
Responses per item25237.500
Density48.255
LongitudinalTRUE

Classification

sampleInternet-based
measurement toolTest
primary language(s)eng

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentStop-Signal Task, expfactory `stop_signal` implementation used in the Self-Regulation Ontology battery
Mean words per item1
Mean characters per item2
Mean characters per response8
Flesch-Kincaid grade level-3.400

Columns

iditemitemcov_delayitemcov_trial_typepositionresprtwave

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("enkavi_2019_stopsignal")
# Python
pip install irw

import irw
df = irw.fetch("enkavi_2019_stopsignal")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_3 v7.0
Redivis dataset DOI10.57761/pqqn-pm43
Manifest pin for this IRW versionv7.0
Metadata sourceirw_meta v23.0