DIF and DDF Detection by Non-Linear Regression Models.
The difNLR package containts method for detection of differential item functioning (DIF) based on non-linear regression. Both uniform and non-uniform DIF effects can be detected when considering one focal group. The method also allows to test the difference in guessing or inattention parameters between reference and focal group. DIF detection method is based either on likelihood-ratio test, or on F-test of submodel. Package also offers method for detection of differential distractor functioning (DDF) based on multinomial log-linear regression model.
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("drabinova/difNLR")Current version on CRAN is 1.2.2. The newest development version available on GitHub is 1.2.2.
To cite difNLR package in publications, please, use:
Drabinova A., Martinkova P., & Zvara K. (2018). difNLR: DIF and DDF detection by non-linear regression models. R package version 1.2.2. https://CRAN.R-project.org/package=difNLR
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. DOI: 10.1111/jedm.12158.
In case you find any bug or just need help with difNLR package, you can leave your message as an issue here or directly contact us at drabinova@cs.cas.cz