Abstract
AbstractThe present work aims at showing that the identification problems (here meant as both issues of empirical indistinguishability and unidentifiability) of some item response theory models are related to the notion of identifiability in knowledge space theory. Specifically, that the identification problems of the 3- and 4-parameter models are related to the more general issues of forward- and backward-gradedness in all items of the power set, which is the knowledge structure associated with IRT models under the assumption of local independence. As a consequence, the identifiability problem of a 4-parameter model is split into two parts: a first one, which is the result of a trade-off between the left-side added parameters and the remainder of the Item Response Function, e.g., a 2-parameter model, and a second one, which is the already well-known identifiability issue of the 2-parameter model itself. Application of the results to the logistic case appears to provide both a confirmation and a generalization of the current findings in the literature for both fixed- and random-effects IRT logistic models.
Funder
Deutsche Forschungsgemeinschaft
Publisher
Springer Science and Business Media LLC
Reference53 articles.
1. Andersen, E. B. (1980). Discrete statistical models with social science applications. Amsterdam: North-Holland.
2. Azevedo, C. L. N. (2009). Observations on the identification and interpretation of the 3PL IRT model. Measurement, 7(2), 89–91.
3. Baker, F. B., & Kim, S.-H. (2004). Item response theory: Parameter estimation techniques. CRC Press.
4. Bamber, D., & Van Santen, J. P. H. (2000). How to assess a model’s testability and identifiability. Journal of Mathematical Psychology, 44(1), 20–40.
5. Barton, M.A. & Lord, F.M. (1981). An upper asymptote for the three-parameter logistic item-response model. RR-81-20 Princeton: Educational Testing Service.