Title: Nonparametric Comparison of Characteristic Curves for DIF Detection
Authors: Adéla Drabinová, Patrícia Martinková
Affiliation: Faculty of Mathematics and Physics, Charles University; Faculty
of Education, Charles University; Institute of Computer Science, Czech Academy
of Sciences
Abstract:
Many methods for detection of differential item functioning (DIF) are derived
from comparison of item characteristic curves. Most of these approaches are
limited in detection of DIF caused either by difference in difficulty or
discrimination parameters with the exception of 3-4 parametric logistic IRT
(Birnbaum, 1968; Barton & Lord, 1981) and non-IRT models (Drabinová &
Martinková, 2017). We propose a novel approach using kernel smoothing
estimation based on nearest neighbors. We argue that newly proposed approach
has a great application potential, as it also considers the differences
between groups in probability of guessing correct answer or in probability of
inattention when answering.
References:
Barton, M. A., & Lord, F. M. (1981). An upper asymptote for the
three-parameter logistic item-response model. ETS Research Report Series,
1981(1), 1-8.
Birnbaum, A. (1968). Some latent trait models and their use in inferring an
examinee's ability. Statistical theories of mental test scores.
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.