kay_2025_antonyms
69,600 responses from 1,200 respondents to 58 items.
About this table
| Description | Semantic Antonyms Data-Quality Probe |
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| Reference | ay, C.S. Why you shouldn’t trust data collected on MTurk. Behav Res 57, 340 (2025). |
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| DOI | 10.3758/s13428-025-02852-7 |
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| Licence | Permission via Email |
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| Source data | https://osf.io/frwq4/files/osfstorage?view_only=2e9d981a2df1411d8971a120ae75df06 |
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Size and shape
| Responses | 69,600 |
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| Respondents | 1,200 |
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| Items | 58 |
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| Response categories | 7 |
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| Responses per respondent | 58 |
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| Responses per item | 1,200 |
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| Density | 1 |
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| Longitudinal | FALSE |
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Classification
| age range | Adult (18+) |
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| sample | Internet-based |
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| construct type | Behavioral, Personality |
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| measurement tool | Survey/questionnaire |
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| item format | Likert Scale/selected response |
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| primary language(s) | ger |
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| construct name | Semantic Antonyms Data-Quality Probe |
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Columns
cov_att_chkcov_culturecov_educationcov_gendercov_incomecov_poli_catcov_poli_contcov_ses_1cov_sourceiditemitemcov_pairitemcov_polarityresp
Get the data
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("kay_2025_antonyms")
# Python
pip install irw
import irw
df = irw.fetch("kay_2025_antonyms")
Version and provenance
| IRW version | v393 |
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| Redivis dataset | item_response_warehouse_5 v4.0 |
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| Redivis dataset DOI | 10.57761/yvjw-0981 |
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| Manifest pin for this IRW version | v4.0 |
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| Metadata source | irw_meta v23.0 |
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