45,214 responses from 1,222 respondents to 37 items.
| Description | The “Reading the Mind in the Eyes” Test Shows Poor Psychometric Properties in a Large, Demographically Representative U.S. Sample |
|---|---|
| Reference | Higgins, W. C., Polito, V., Ross, R. M., & Langdon, R. (2022, September 8). 1. Theory of Mind and emotion recognition in the Reading the Mind in the Eyes test: a factor analysis. Retrieved from osf.io/8jtn9 |
| DOI | 10.1177/10731911221124342 |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/8jtn9/overview |
| Responses | 45,214 |
|---|---|
| Respondents | 1,222 |
| Items | 37 |
| Response categories | 4 |
| Responses per respondent | 37 |
| Responses per item | 1,222 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Internet-based |
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Constructed Response |
| primary language(s) | eng |
| construct name | Reading the Mind in the Eyes Test |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | The “Reading the Mind in the Eyes” Test Shows Poor Psychometric Properties in a Large, Demographically Representative U.S. Sample |
|---|---|
| Mean words per item | 22 |
| Mean characters per item | 132 |
| Mean characters per response | 8.338 |
| Flesch-Kincaid grade level | 10.154 |
cov_agecov_dem_agecov_dem_educationcov_dem_ethnicitycov_dem_gendercov_dem_god_4cov_ethnicitycov_genderiditemresprt
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("rmet_higgins_2022_rmet")
# Python
pip install irw
import irw
df = irw.fetch("rmet_higgins_2022_rmet")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v19.0 |
| Redivis dataset DOI | 10.57761/qtx5-4m80 |
| Manifest pin for this IRW version | v19.0 |
| Metadata source | irw_meta v23.0 |