碩士 / 國立中正大學 / 心理學所 / 97 / The two-parameter logistic model with ability-based guessing (2PL-AG) model was proposed in this study, which is extended from the 1PL-AG model which not only incorporate the chances of a correct guess being dependent on ability and difficulty (Mart?n, del Pino, & De Boeck, 2006), but comprise a discrimination parameter in the items. To estimate the parameters of the model, Markov chain Monte Carlo (MCMC) method was used in this study. Furthermore, a computerized adaptive testing (CAT) algorithm based on the 2PL-AG model (called 2PL-AG-CAT) was constructed. Through Monte Carlo simulation study, the performance on latent trait estimation of 2PL-AG-CAT was compared to that based on 1PL-AG model (called 1PL-AG-CAT) and 3PL model (called 3PL -CAT). The results indicated that the 2PL-AG in highly ability-base guessing was better than 3PL。And the 2PL-AG was more efficient than 3PL model in term of slightly lower bias and root mean square error (RMSE).
| Identifer | oai:union.ndltd.org:TW/097CCU05071037 |
| Date | January 2009 |
| Creators | Hsuan-Jui Shih, 石軒瑞 |
| Contributors | Wen Chung Wang, Shu-Ying Chen, 王文中, 陳淑英 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 47 |
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