https://github.com/adelahladka/difnlr
DIF and DDF Detection by Non-Linear Regression Models.
https://github.com/adelahladka/difnlr
differential-item-functioning item-analysis psychometrics r statistics
Last synced: about 1 year ago
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DIF and DDF Detection by Non-Linear Regression Models.
- Host: GitHub
- URL: https://github.com/adelahladka/difnlr
- Owner: adelahladka
- Created: 2016-11-15T14:24:15.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2025-03-20T20:53:13.000Z (over 1 year ago)
- Last Synced: 2025-03-29T05:23:29.216Z (about 1 year ago)
- Topics: differential-item-functioning, item-analysis, psychometrics, r, statistics
- Language: R
- Homepage:
- Size: 6.15 MB
- Stars: 6
- Watchers: 1
- Forks: 3
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md
Awesome Lists containing this project
README
# difNLR
DIF and DDF Detection by Non-Linear Regression Models.
[](https://github.com/adelahladka/difNLR/actions)
[](https://CRAN.R-project.org/package=difNLR)
## Description
The `difNLR` package provides methods for detecting differential item
functioning (DIF) using non-linear regression models. Both uniform and
non-uniform DIF effects can be detected when considering a single focal group.
Additionally, the method allows for testing differences in guessing or
inattention parameters between the reference and focal group. DIF detection is
performed using either a likelihood-ratio test, an F-test, or Wald's test of a
submodel. The software offers a variety of algorithms for estimating item
parameters.
Furthermore, the `difNLR` package includes methods for detecting differential
distractor functioning (DDF) using multinomial log-linear regression model. It
also introduces DIF detection approaches for ordinal data via adjacent category
logit and cumulative logit regression models.
## Installation
The easiest way to get `difNLR` package is to install it from CRAN:
```
install.packages("difNLR")
```
Or you can get the newest development version from GitHub:
```
# install.packages("devtools")
devtools::install_github("adelahladka/difNLR")
```
## Version
Current version on [**CRAN**](https://CRAN.R-project.org/package=difNLR) is
1.5.1-1. The newest development version available on
[**GitHub**](https://github.com/adelahladka/difNLR) is 1.5.1-2.
## Reference
To cite `difNLR` package in publications, please, use:
- Hladka, A. & Martinkova, P. (2020). difNLR: Generalized logistic regression models for DIF and DDF detection.
The R Journal, 12(1), 300--323,
https://doi.org/10.32614/RJ-2020-014
- Drabinova, 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,
https://doi.org/10.1111/jedm.12158
To cite new estimation approaches provided in the `difNLR()` function, please, use:
- Hladka, A., Martinkova, P., & Brabec, M. (2024). New iterative algorithms for estimation of item functioning.
Journal of Educational and Behavioral Statistics.
Online first, https://doi.org/10.3102/10769986241312354
## Try online
You can try some functionalities of the `difNLR` package
[online](https://shiny.cs.cas.cz/ShinyItemAnalysis/) using
[`ShinyItemAnalysis`](https://github.com/patriciamar/ShinyItemAnalysis)
application and package and its DIF/Fairness section.
## Getting help
In case you find any bug or just need help with the `difNLR` package, you can leave
your message as an issue here or directly contact us at hladka@cs.cas.cz