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

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, difNLR.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).made in the build script
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
Respondent covariates
cov_genderCovariate not traced

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("difnlr_msatb")
# Python
pip install irw

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

How to cite

@article{Drabinov__2017, title={Detection of Differential Item Functioning with Nonlinear Regression: A Non‐IRT Approach Accounting for Guessing}, volume={54}, ISSN={1745-3984}, url={http://dx.doi.org/10.1111/jedm.12158}, DOI={10.1111/jedm.12158}, number={4}, journal={Journal of Educational Measurement}, publisher={Wiley}, author={Drabinová, Adéla and Martinková, Patrícia}, year={2017}, month=dec, pages={498–517} }

Version and provenance

IRW versionv566
Redivis datasetitem_response_warehouse v70.0
Redivis dataset DOI10.57761/4qxs-pq87
Manifest pin for this IRW versionv70.0
Metadata sourceirw_meta v43.0