rmet_higgins_2022_aq

34,216 responses from 1,222 respondents to 28 items.

About this table

DescriptionAutism Spectrum Quotient
ReferenceHiggins, 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
DOI10.1177/10731911221124342
LicenceCC BY 4.0
Source datahttps://osf.io/8jtn9/overview

Size and shape

Responses34,216
Respondents1,222
Items28
Response categories4
Responses per respondent28
Responses per item1,222
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleInternet-based
construct typeDevelopmental, Personality
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameAutism Spectrum Quotient

Item text

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

InstrumentAutism Spectrum Quotient
Mean words per item9.893
Mean characters per item54.750
Mean characters per response16.500
Flesch-Kincaid grade level5.819

Columns

cov_agecov_dem_agecov_dem_educationcov_dem_ethnicitycov_dem_gendercov_dem_god_4cov_ethnicitycov_genderiditemresp

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("rmet_higgins_2022_aq")
# Python
pip install irw

import irw
df = irw.fetch("rmet_higgins_2022_aq")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_2 v19.0
Redivis dataset DOI10.57761/qtx5-4m80
Manifest pin for this IRW versionv19.0
Metadata sourceirw_meta v23.0