CQTMS_Hur_2023

122,720 responses from 767 respondents to 160 items.

About this table

DescriptionStrengthening the Reporting of Observational studies in Epidemiology(STROBE)
ReferenceHur, Y., & Seo, D. G. (2023). Development of a character qualities test for medical students in Korea using polytomous item response theory and factor analysis: a preliminary scale development study. Journal of Educational Evaluation for Health Professions, 20. Yera Hur; Dong Gi Seo, 2023, "Development of a character qualities test for medical students in Korea using polytomous item response theory and factor analysis: a preliminary scale development study", https://doi.org/10.7910/DVN/UE55JT, Harvard Dataverse, V1
LicenceCC0 1.0
Source datahttps://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/UE55JT

Size and shape

Responses122,720
Respondents767
Items160
Response categories5
Responses per respondent160
Responses per item767
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational, Targeted/specific
construct typeBehavioral
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)kor
construct nameDevelopment of a character qualities test for medical students in Korea using polytomous item response theory and factor analysis: a preliminary scale development study

Item text

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

InstrumentCharacter Qualities Test for Medical Students (SPHER3C), 160-item preliminary form
Mean words per item4.269
Mean characters per item19.762
Mean characters per response10.200
Flesch-Kincaid grade level2.159

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, CQTMS_Hur_2023.R. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.

ColumnWhat it isSource column
IRW standard columns
idIRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).Person
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script

What item codes and covariate values stand for is in the codebook released with the source data.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("CQTMS_Hur_2023")
# Python
pip install irw

import irw
df = irw.fetch("CQTMS_Hur_2023")

How to cite

@misc{https://doi.org/10.7910/dvn/ue55jt,
  doi = {10.7910/DVN/UE55JT},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/UE55JT},
  author = {{Yera Hur} and Seo, Dong Gi},
  keywords = {Medicine, Health and Life Sciences},
  title = {Development of a character qualities test for medical students in Korea using polytomous item response theory and factor analysis: a preliminary scale development study},
  publisher = {Harvard Dataverse},
  year = {2023}
}

Version and provenance

IRW versionv549
Redivis datasetitem_response_warehouse v70.0
Redivis dataset DOI10.57761/4qxs-pq87
Manifest pin for this IRW versionv70.0
Metadata sourceirw_meta v39.0