ISSN 1671-3710
CN 11-4766/R

Advances in Psychological Science ›› 2014, Vol. 22 ›› Issue (3): 540-548.doi: 10.3724/SP.J.1042.2014.00540

• Research Methods • Previous Articles     Next Articles

The Mixture Item Response Theory Models and Its Application Traces

WANG Xia;TAN Guohua;WANG Xu;ZHANG Minqiang;LUO Cong   

  1. (1 Center for studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China) (2 Teaching Research Office of Guangzhou Education Bureau, Guangzhou 510030, China) (3 Guangzhou Municipal Education Information Center, Guangzhou 510030, China)
  • Received:2013-05-25 Online:2014-03-15 Published:2014-03-15
  • Contact: ZHANG Minqiang


Item response theory (IRT) is a modern measurement theory for accurately estimating individuals’ ability, and latent class analysis (LCA) is a statistical technique used to identify subtypes of individuals, which is based on statistic models. Mixture item response theory (Mixture IRT) combining LCA and IRT is able to classify the subjects as well as quantifying their traits. The concept and principle of Mixture IRT is elaborated in this paper. Besides, several common mixed models are introduced here, such as the mixed Rasch model (MRM), a mixture version of the nominal response model (mNRM) and a mixture version of the partial credit model (mPCM). Furthermore, different parameter estimation methods are described and the application traces in psychological test of Mixture IRT is evaluated from the perspectives of classifying psychological or behavioral traits, detecting differential item functioning and estimating test validity.

Key words: item response theory (IRT), latent class analysis (LCA), Mixture IRT, latent structure