eammi_grahe_2018_disability_identity

25,471 responses from 1,978 respondents to 15 items.

About this table

DescriptionDisability Identity
ReferenceGrahe, J. E., Chalk, H. M., Cramblet Alvarez, L. D., Faas, C., Hermann, A., Ph.D., McFall, J. P., & Molyneux, K. (2019, June 13). EAMMi2 Public Data. https://doi.org/10.17605/OSF.IO/QTQPB
DOI10.5334/jopd.38
LicencePermission via Email
Source datahttps://osf.io/qtqpb/overview

Size and shape

Responses25,471
Respondents1,978
Items15
Response categories5
Responses per respondent12.877
Responses per item1698.067
Density0.858
LongitudinalTRUE

Classification

age rangeAdult (18+)
sampleGeneral/non-specific
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameDisability Identity

Item text

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

InstrumentDisability Identity
Mean words per item7.800
Mean characters per item43.067
Mean characters per response7.400
Flesch-Kincaid grade level8.127

Columns

cov_agecov_armed_forces_yearscov_childhood_statecov_educationcov_gendercov_incomecov_political_ideologycov_political_partycov_president_supportcov_racecov_schoolcov_siblingscov_us_residentcov_years_in_usdateiditemresprt

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("eammi_grahe_2018_disability_identity")
# Python
pip install irw

import irw
df = irw.fetch("eammi_grahe_2018_disability_identity")

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