96,912 responses from 523 respondents to 48 items.
| Description | Attention Network Task flanker component (congruent/incongruent/neutral), trial-level accuracy + RT, N=523, baseline + retest waves |
|---|---|
| Reference | Enkavi, 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 |
| DOI | 10.1073/pnas.1818430116 |
| Licence | CC BY 4.0 |
| Source data | https://github.com/IanEisenberg/Self_Regulation_Ontology/tree/master/Data |
| Responses | 96,912 |
|---|---|
| Respondents | 523 |
| Items | 48 |
| Response categories | 2 |
| Responses per respondent | 185.300 |
| Responses per item | 2,019 |
| Density | 3.860 |
| Longitudinal | TRUE |
| sample | Internet-based |
|---|---|
| measurement tool | Test |
| primary language(s) | eng |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Attention Network Task (ANT), expfactory `attention_network_task` implementation used in the Self-Regulation Ontology battery |
|---|---|
| Mean words per item | 19.250 |
| Mean characters per item | 75.625 |
| Mean characters per response | 8 |
| Flesch-Kincaid grade level | 4.366 |
iditemitemcov_conditionitemcov_cuepositionresprtwave
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("enkavi_2019_ant_flanker")
# Python
pip install irw
import irw
df = irw.fetch("enkavi_2019_ant_flanker")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v7.0 |
| Redivis dataset DOI | 10.57761/pqqn-pm43 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |