The difNLR package contains 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, F-test, or Wald's test of a submodel. Package also offers methods for detection of differential distractor functioning (DDF) based on multinomial log-linear regression model and newly methods for DIF detection among ordinal data via adjacent category logit and cumulative logit regression models.
Package: difNLR Type: Package Version: 1.3.7 Date: 2021-01-07 Depends: R (>= 3.1) Imports: CTT, ggplot2 (>= 2.2.1), grDevices, methods, msm, nnet, plyr, reshape2, stats, VGAM Suggests: ShinyItemAnalysis License: GPL-3 BugReports: https://github.com/adelahladka/difNLR/issues Encoding: UTF-8
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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, 10.1111/jedm.12158.
Hladka, A. & Martinkova, P. (2020). difNLR: Generalized logistic regression models for DIF and DDF detection. The R journal, 12(1), 300--323, 10.32614/RJ-2020-014.
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Report bugs at https://github.com/adelahladka/difNLR/issues