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.