ISSN 1671-3710
CN 11-4766/R

Advances in Psychological Science ›› 2015, Vol. 23 ›› Issue (1): 150-157.doi: 10.3724/SP.J.1042.2015.00150

• Research Methods • Previous Articles     Next Articles

The Development and Application of Higher-Order Item Response Models

CHEN Feipeng1; ZHAN Peida1,4; WANG Lijun1; CHEN Chunxiao2; CAO Mao3   

  1. (1 Department of Psychology, Zhejiang Normal University, Jinhua 321004, China) (2 Hangzhou NO.4 High School, Hangzhou 310002, China) (3 Hangzhou NO.9 High School, Hangzhou 310020, China) (4 National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China)
  • Received:2014-01-07 Online:2015-01-15 Published:2015-01-15
  • Contact: WANG Lijun, E-mail: frankwlj@163.com

Abstract:

When measuring hierarchical latent trait, the standard IRT models have low efficiency in estimating item parameters and ability parameters. Without considering hierarchical structure, MIRT models have a high efficiency in estimating the first-order latent traits. It is not suitable for dealing with hierarchical latent trait. The HO-IRM not only can produce more accurate item parameter and ability parameters estimates, but also can obtain the first-order and high-order latent traits. The currently-existing HO-IRM includes high-order DINA model, high-order two parameter normal ogive hierarchical model, high-order logistic model, high-order polytomous items model and higher-order testlet model. In the future HO-IRM study, attention must be paid to the multi-level HO-IRM, HO-IRM within an item in the multidimensional situation and high-order cognitive diagnostic models.

Key words: IRT, HO-IRM, MIRM, first-order latent traits, high-order latent traits