eammi_grahe_2018_stress

30,763 responses from 3,182 respondents to 12 items.

About this table

DescriptionPerceived Stress
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

Responses30,763
Respondents3,182
Items12
Response categories5
Responses per respondent9.668
Responses per item2563.583
Density0.806
LongitudinalTRUE

Classification

age rangeAdult (18+)
sampleGeneral/non-specific
construct typeAffective/mental health
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct namePerceived Stress

Item text

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

InstrumentPerceived Stress
Mean words per item9.083
Mean characters per item54
Mean characters per response4.833
Flesch-Kincaid grade level36.507

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_stress")
# Python
pip install irw

import irw
df = irw.fetch("eammi_grahe_2018_stress")

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