The Application of the Random-Threshold Generalized Graded Unfolding Model to Computerized Adaptive Testing and Computerized Classification Testing

• Main Authors: Chen-Wei Liu, 劉振維
• Other Authors: Wen-Chung Wang
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/70685125318945334528

碩士 === 國立中正大學 === 心理學所 === 97 === The random-threshold generalized graded unfolding model (RTGGUM) was employed in this study(Wu & Wang, 2009). This model takes the randomness in the threshold over persons into account by treating it as random-effect and adding a random variable for each threshold. To investigate the applicability of the RTGGUM more thoroughly, it was further applied to both computerized adaptive testing (CAT) and computerized classification testing (CCT). By taking the random-threshold as another dimension, the RTGGUM-CAT can be regarded as a special case of multidimensional adaptive testing and both the latent trait and random thresholds were estimated simultaneously. On the other hand, the focus of RTGGUM-CCT is on the accuracy of classification and therefore the random thresholds are viewed as randomness. The results indicated that the existence of random thresholds would lead to inaccurate latent trait estimates, as well as increase the classification errors. Therefore, the reliability of latent trait estimates and the accuracy of classification are doubtful if the random thresholds were ignored. The related issues about the application of RTGGUM in CAT and CCT are discussed.