Modeling local item dependence in C-tests with the loglinear Rasch model

Abstract

C-tests are gap-filling tests mainly used as rough and economical measures of second-language proficiency for placement and research purposes. A C-test usually consists of several short independent passages where the second half of every other word is deleted. Owing to their interdependent structure, C-test items violate the local independence assumption of IRT models. This poses some problems for IRT analysis of C-tests. A few strategies and psychometric models have been suggested and employed in the literature to circumvent the problem. In this research, a new psychometric model, namely, the loglinear Rasch model, is used for C-tests and the results are compared with the dichotomous Rasch model where local item dependence is ignored. Findings showed that the loglinear Rasch model fits significantly better than the dichotomous Rasch model. Examination of the locally dependent items did not reveal anything as regards their contents. However, it did reveal that 50% of the dependent items were adjacent items. Implications of the study for modeling local dependence in C-tests using different approaches are discussed.