difNLR-package: Detection of Dichotomous Differential Item Functioning (DIF)...

Description Details Note Author(s) References


The difNLR package containts DIF detection method based on Non-Linear Regression. Both uniform and non-uniform DIF effects can be detected when considering one focal group. DIF detection method is based either on likelihood-ratio test, or on F-test of submodel. Package also offers DDF detection method based on Multinomial Log-linear Regression model.


Package: difNLR
Type: Package
Version: 1.0.0
Date: 2017-01-19
Depends: R (>= 3.2.2), CTT, ggplot2, methods, nnet, reshape2, stats
License: GPL-3


This package was supported by grant funded by Czech Science foundation under number GJ15-15856Y.


Adela Drabinova
Institute of Computer Science, The Czech Academy of Sciences
Faculty of Mathematics and Physics, Charles University

Patricia Martinkova
Institute of Computer Science, The Czech Academy of Sciences

Karel Zvara
Faculty of Mathematics and Physics, Charles University


Drabinova, A. and Martinkova P. (2016). Detection of Differenctial Item Functioning Based on Non-Linear Regression, Technical Report, V-1229, http://hdl.handle.net/11104/0259498.

Kingston, N., Leary, L., and Wightman, L. (1985). An Exploratory Study of the Applicability of Item Response Theory Methods to the Graduate Management Admission Test. ETS Research Report Series, 1985(2) : 1-64.

Martinkova, P., Drabinova, A., Liaw Y.-L., Sanders E. A., McFarland J. L., Price R. M. (2016). Using DIF Analysis to Reveal Potential Equity Gaps in Conceptual Assessments. In review.

Swaminathan, H. and Rogers, H. J. (1990). Detecting Differential Item Functioning Using Logistic Regression Procedures. Journal of Educational Measurement, 27, 361-370.

Vlckova, K. (2014). Test and Item Fairness (Unpublished master's thesis).

difNLR documentation built on May 19, 2017, 11:48 a.m.

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