difnlr_msatb

28,140 responses from 1,407 respondents to 20 items.

About this table

DescriptionResponses to Czech medical school admissions exam
ReferenceDrabinova, A. & Martinkova, P. (2017). Detection of differential item functioning with nonlinear regression: A non-IRT approach accounting for guessing. Journal of Educational Measurement, 54(4), 498–517, doi: 10.1111/jedm.12158.
DOI10.1111/jedm.12158
LicenceGPL-3.0
Source datahttps://cran.r-project.org/web/packages/difNLR/index.html

Size and shape

Responses28,140
Respondents1,407
Items20
Response categories2
Responses per respondent20
Responses per item1,407
Density1
LongitudinalFALSE

Classification

age rangeChild (<18y)
child age (for child-focused studies)Adolescent (12-18y)
sampleTargeted/specific
construct typeOpinion/attitude
measurement toolTest
item formatLikert Scale/selected response
primary language(s)eng
construct nameDIF and DDF Detection by Non-Linear Regression Models

Columns

cov_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("difnlr_msatb")
# Python
pip install irw

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

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse v53.0
Redivis dataset DOI10.57761/4g08-xt41
Manifest pin for this IRW versionv53.0
Metadata sourceirw_meta v23.0