A study of unidimensional IRT models for items scored in multiple ordered response catagories
By: by Olesya Falenchuk.
Published: 2006
Language: eng
Number of pages: 266
ISBN-13: 9780494218136
Subjects: Item response theory -- Mathematical models.; Educational tests and measurements.; Psychological tests.
Description: This study has demonstrated that (1) the CRM, GRM and GPCM belong to three distinct classes of IRT models that do not overlap, (2) the probability of item responses is estimated differently by the three models, (3) the amount of difference between ISRFs obtained from the three models for a specific item depends on the type of distribution of examinee responses across the score categories, (4) the differences among ISRFs obtained from the three models mostly appear at the ends of the ability continuum, (5) different performance of the models at the item level does not necessarily result in different accuracy of ability estimates obtained from the three models.The underlying mechanism of modeling polytomous item response data involves multiple dichotomizations of item response categories into item step response functions (ISRFs). ISRFs of an item have similar shape (monotonically increasing) and can be modeled with simple logistic functions. ISRFs can be formed by using cumulative probability, adjacent category and continuation ratio logits. Depending on the ISRFs type, polytomous IRT models can be classified into cumulative probability, adjacent category and continuation ratio models.Very few studies have directly compared models with different types of ISRFs. Moreover, a comparative study of the two most widely used polytomous IRT models with different types of ISRFs (the graded response model (GRM) and the generalized partial credit model (GPCM)) and the recently developed continuation ratio model (CRM) was never conducted before. The purpose of this study was to compare the GRM, GPCM, and CRM under different conditions (sample sizes, test lengths, number of item score categories). These models were applied to items with different distributions of examinees' responses across score categories.Although the results clearly show the differences among the three models, this study does not provide strong evidence for the superiority of one model over another. Even though the models appear to perform differently at the item level, the ability estimates are only slightly influenced by the model choice.
Notes: Source: Dissertation Abstracts International, Volume: 68-01, Section: A, page: 0163.

Thesis (Ph.D.)--University of Toronto, 2006.

Includes bibliographical references (leaves 150-159).

Electronic version licensed for access by U. of T. users.